{
  "data": {
    "a": {
      "slug": "eden-ai",
      "name": "Eden AI",
      "vendor": "Eden AI SAS",
      "vendorUrl": "https://www.edenai.co",
      "kind": "router",
      "category": "inference",
      "summary": "Eden AI is a French AI gateway with one OpenAI-compatible API key for about 1,000 chat and expert models from 80 or more providers, including OCR, speech, translation and image analysis, with an EU-only endpoint and a hosted MCP server.",
      "url": "https://www.anchorterminal.com/tools/eden-ai",
      "markdownUrl": "https://www.anchorterminal.com/tools/eden-ai.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/eden-ai.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/eden-ai.json",
      "dns": "eden-ai.grade.anchorterminal.com",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://mcp.edenai.run/mcp",
      "packages": [],
      "auth": "api-key",
      "authNotes": "Bearer key created in the dashboard at app.edenai.run after a browser signup. Keys carry budgets, expiry and attribution, can be managed through a key API, and can be limited to chosen models by deny-by-default guardrails. The MCP server takes the same key in the Authorization header.",
      "pricing": "usage",
      "pricingNotes": "Provider list prices with no markup plus a 5.5% platform fee applied when buying credits. Prepaid credits through Stripe by card, PayPal or bank transfer, with optional auto-refill. Some models are billed $0 for tests. The Advanced plan is by quote.",
      "priceSummary": "5.5% fee",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in llms.txt, the OpenAPI spec, the pricing pages or the agent catalogue (checked 2026-11-06). Credits are bought through Stripe.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://www.edenai.co/docs",
      "llmsTxt": "https://www.edenai.co/llms.txt",
      "openapi": "https://api.edenai.run/v3/docs/openapi.json",
      "capabilities": [
        "inference.router",
        "inference.llm",
        "embed.text",
        "translate.text",
        "translate.documents",
        "docs.ocr",
        "speech.stt",
        "speech.tts",
        "image.generate",
        "guard.moderation"
      ],
      "tags": [
        "hosted",
        "router",
        "openai-compatible",
        "usage-priced",
        "prepaid",
        "mcp",
        "remote-mcp",
        "api-key",
        "llms-txt",
        "openapi",
        "eu",
        "eu-region",
        "soc2",
        "iso27001",
        "batch",
        "closed-source"
      ],
      "lastRelease": "2026-11-05",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.9,
        "grade": "C",
        "agentReady": false,
        "rank": 675,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 22,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 75,
          "maintenance": 58,
          "payments": 30,
          "reliability": 33,
          "schema": 81,
          "security": 82,
          "transparency": 55
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.",
        "bestFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.",
        "strengths": [
          "OpenAI-compatible v3 API with an OpenAPI 3.1 spec and a keyless model catalogue with prices and regions",
          "EU endpoint that refuses models not cleared for European processing with HTTP 451",
          "Content isn't stored or used for training by default, with opt-in logs and enforceable Zero Data Retention",
          "Per-key budgets, expiry and deny-by-default guardrails, plus a key management API",
          "Hosted MCP server exposing OCR, speech, translation, web search and other expert models as tools"
        ],
        "weaknesses": [
          "No public status page, incident history or SLA found",
          "The rate-limits page says 10 requests a second and the plans page says 7, raisable to 15",
          "No public changelog or deprecation policy",
          "The OpenAPI spec documents few error responses",
          "Credits are prepaid through Stripe with a 5.5% platform fee on every purchase"
        ],
        "agentNotes": [
          "Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them",
          "Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed",
          "Set max_tokens to 500 or more for reasoning models, or the answer can come back empty",
          "Pass a fallbacks list so a provider 429 or error retries inside one request",
          "Poll check_job for MCP tools marked long-running instead of calling them again"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.9
          }
        ],
        "editorialScores": {
          "ergonomics": 75,
          "maintenance": 58,
          "payments": 30,
          "reliability": 33,
          "schema": 81,
          "security": 82,
          "transparency": 65
        },
        "provenanceScore": 44,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "http": "curl https://api.edenai.run/v3/models",
        "claudeCode": "claude mcp add edenai --transport http https://mcp.edenai.run/mcp --header \"Authorization: Bearer $EDENAI_API_KEY\"",
        "config": {
          "mcpServers": {
            "edenai": {
              "headers": {
                "Authorization": "Bearer YOUR_EDENAI_API_KEY"
              },
              "url": "https://mcp.edenai.run/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/inference.router",
        "tool": "https://letme.dev/eden-ai"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Platform fee on credit purchases",
          "unit": "pct",
          "usd": 5.5,
          "note": "On top of provider list prices, which carry no markup"
        }
      ],
      "provenance": {
        "legalEntity": "Eden AI SAS",
        "domain": "edenai.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": false,
        "terms": "https://www.edenai.co/terms",
        "privacy": "https://www.edenai.co/privacy",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-11-06",
        "notes": [
          "The terms, last updated 22 October 2026, name Eden AI SAS, share capital €4,992, 19 rue Louis Guérin, 69100 Villeurbanne, France, under French law with courts in Lyon.",
          "The API and MCP server run on edenai.run, a second domain of the same company, while the site and docs are on edenai.co.",
          "robots.txt on www.edenai.co allows all agents and carries `Content-Signal: search=yes, ai-input=yes, ai-train=yes`.",
          "/.well-known/security.txt returns 404. No status page is linked, and status.edenai.co didn't resolve on 6 November 2026.",
          "RDAP for edenai.co wasn't read: rdap.org rate-limited us and the .co registry server wasn't tried."
        ],
        "score": 44
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/eden-ai.json",
      "live": {
        "slug": "eden-ai",
        "probe": {
          "target": "https://mcp.edenai.run/mcp",
          "method": "get",
          "lastAt": "2026-11-07T19:22:04.810042763Z",
          "lastOk": true,
          "lastStatus": 405,
          "lastMs": 58,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 50,
          "p95ms24h": 129,
          "samples24h": 210,
          "samples30d": 210,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "securityTxt": {
          "url": "https://edenai.co/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-07T15:59:41.694549385Z"
        },
        "llmsTxt": {
          "url": "https://www.edenai.co/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:20.299431316Z"
        },
        "pages": [
          {
            "url": "https://www.edenai.co/privacy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-07T14:28:13.706474894Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "21a1da47a2ce"
          },
          {
            "url": "https://www.edenai.co/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-07T14:28:15.881335606Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "9cd0db8f0f61"
          }
        ],
        "mcpTools": {
          "url": "https://mcp.edenai.run/mcp",
          "checkedAt": "2026-11-07T01:44:01.27972989Z",
          "status": "ok",
          "protocol": "2025-11-25",
          "tools": [
            {
              "name": "list_models",
              "description": "List available providers/models and their pricing.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "tool": {
                    "anyOf": [
                      {
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Optional tool name (as returned by tools/list) to filter on."
                  }
                },
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "list_voices",
              "description": "List the voices a text-to-speech model accepts, for audio_tts's 'voice'.\n\nThe model's default voice comes first.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "gender": {
                    "anyOf": [
                      {
                        "enum": [
                          "female",
                          "male",
                          "unknown"
                        ],
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Keep voices of this gender."
                  },
                  "language": {
                    "anyOf": [
                      {
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Keep voices speaking this language: 'fr' matches every region,\n'fr-CA' only that locale. Multilingual voices are always kept."
                  },
                  "limit": {
                    "default": 50,
                    "description": "Most voices to return (default 50, max 200); 'total' counts every match.",
                    "type": "integer"
                  },
                  "model": {
                    "description": "The audio_tts model, as 'provider' or 'provider/model' (e.g. 'amazon/neural').",
                    "type": "string"
                  }
                },
                "required": [
                  "model"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "upload_file",
              "description": "Upload a file to Eden AI and get a file ID to use in other tools.\n\nOnly needed for local file content. If you already have a public URL\nfor the file, pass that URL directly to the tool's file parameter\ninstead — no upload needed.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "content_base64": {
                    "description": "The file content, base64-encoded.",
                    "type": "string"
                  },
                  "expires_in_days": {
                    "default": 30,
                    "description": "How long Eden AI keeps the file (1-30, default 30).",
                    "type": "integer"
                  },
                  "filename": {
                    "description": "Name with extension (used to detect the file type).",
                    "type": "string"
                  }
                },
                "required": [
                  "content_base64",
                  "filename"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "check_job",
              "description": "Get the status/result of an async job started by a long-running tool.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "job_id": {
                    "description": "The job id returned when the job was submitted.",
                    "type": "string"
                  }
                },
                "required": [
                  "job_id"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "manage_collections",
              "description": "Create and manage collections: stored sets of items (e.g. faces) that a tool searches against. Tools that take a collection_id: image_face_recognition. Flow: create, then add_item once per file (returns the item ids it indexed), then call the tool with the collection_id; delete when done. Arguments per action: create(model, tool?, name?); list(tool?, model?, page?); get, delete, list_items(collection_id); add_item(collection_id, file); delete_item(collection_id, item_id).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "action": {
                    "enum": [
                      "create",
                      "list",
                      "get",
                      "delete",
                      "add_item",
                      "list_items",
                      "delete_item"
                    ],
                    "type": "string"
                  },
                  "collection_id": {
                    "description": "From create or list.",
                    "type": "string"
                  },
                  "file": {
                    "description": "File to add (add_item). Pass a file ID (UUID) from upload_file, or a direct file URL.",
                    "type": "string"
                  },
                  "item_id": {
                    "description": "Item to delete (delete_item), from add_item or list_items.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Provider the collection binds to (create; list filter). image_face_recognition: amazon.",
                    "type": "string"
                  },
                  "name": {
                    "description": "Optional label (create).",
                    "type": "string"
                  },
                  "page": {
                    "description": "Result page (list).",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "tool": {
                    "description": "Tool the collection serves (create; list filter). Defaults to image_face_recognition.",
                    "enum": [
                      "image_face_recognition"
                    ],
                    "type": "string"
                  }
                },
                "required": [
                  "action"
                ],
                "type": "object"
              }
            },
            {
              "name": "audio_speech_to_text",
              "description": "Speech Recognition (or speech to text or voice to text) can recognize and transcribe spoken words (voice),  that will be converted to text with or without diarization. It is also possible to filter profanity. The type of files allowed are: mp3, wav, m4a. If convert_to_wav option is set to true, then you can transcribe any type of audio or video files. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Audio file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: audio/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Language code in ISO format (e.g., 'en', 'fr', 'es')",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, assembly, deepgram, deepgram/base, deepgram/enhanced, deepgram/nova-3, gladia, google, gradium, gradium/stt-translate, greenpt, greenpt/green-s, greenpt/green-s-pro, microsoft, mistral, mistral/voxtral-mini-2602, mistral/voxtral-mini-latest, mistral/voxtral-mini-transcribe-3, mistral/voxtral-small-transcribe-3, openai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "profanity_filter": {
                    "default": false,
                    "description": "Whether to filter profanity and replace inappropriate words with a series of asterisks",
                    "type": "boolean"
                  },
                  "speakers": {
                    "default": 2,
                    "description": "Number of speakers present in the audio",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "vocabulary": {
                    "description": "List of words or composed words to be detected by the speech to text engine",
                    "items": {
                      "type": "string"
                    },
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "audio_tts",
              "description": "Text-to-speech (TTS) is a technology that converts written text into spoken audio, enabling computers and digital devices to \"read\" text aloud.  It is also known as speech synthesis, read aloud technology, or computer-generated speech.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "audio_format": {
                    "description": "Desired audio format (e.g., 'mp3', 'wav')",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon/neural, amazon/standard, deepgram/aura, deepgram/aura-2, elevenlabs, elevenlabs/eleven_flash_v2, elevenlabs/eleven_flash_v2_5, elevenlabs/eleven_multilingual_v2, elevenlabs/eleven_turbo_v2, elevenlabs/eleven_turbo_v2_5, elevenlabs/eleven_v3, google/casual, google/chirp-hd, google/chirp3-hd, google/gemini-2.5-flash-tts, google/gemini-2.5-pro-tts, google/gemini-3.1-flash-tts-preview, google/neural2, google/news, google/polyglot, google/standard, google/studio, google/wavenet, gradium, microsoft/neural, microsoft/neural-hd, mistral/voxtral-mini-tts-3, openai/gpt-4o-mini-tts, openai/tts-1, openai/tts-1-hd, ovhcloud/nvr-tts-de-de, ovhcloud/nvr-tts-en-us, ovhcloud/nvr-tts-es-es, ovhcloud/nvr-tts-it-it. Call list_models for pricing.",
                    "type": "string"
                  },
                  "speaking_pitch": {
                    "description": "Increase or decrease the speaking pitch by a percentage from -100% to 100%, 0 is normal.",
                    "maximum": 100,
                    "minimum": -100,
                    "type": "integer"
                  },
                  "speaking_volume": {
                    "description": "Increase or decrease the audio volume by a percentage from -100% to 100%, 0 is normal.",
                    "maximum": 100,
                    "minimum": -100,
                    "type": "integer"
                  },
                  "speed": {
                    "description": "Speed multiplier for speech synthesis",
                    "maximum": 4,
                    "minimum": 0.25,
                    "type": "number"
                  },
                  "text": {
                    "description": "Text to convert to speech",
                    "minLength": 1,
                    "type": "string"
                  },
                  "voice": {
                    "description": "Voice to synthesize with: an id or name from list_voices(model=...), matched case-insensitively. Omit it to use the model's default voice. An id the list doesn't know (e.g. your own cloned voice) is sent to the provider unchanged.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_ai_detection",
              "description": "Determine whether an image was generated by AI or is a real photograph or artwork. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble, winstonai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_anonymization",
              "description": "Image Anonymization API, also known as image de-identification or image de-personalization, refers to the process of automatically removing personal or sensitive information from images. The main objective is to protect the privacy and security of individuals who may be depicted in images shared online or used for research purposes. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_background_removal",
              "description": "Background removal is a digital image processing technique designed to seamlessly eliminate the backdrop of a photo, leaving behind only the main subject. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai, clipdrop, photoroom, picsart, sentisight, stabilityai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_deepfake_detection",
              "description": "Detect whether a face in a real photo has been swapped or manipulated (face-swap deepfakes). For fully AI-generated images, use AI Image Detection instead. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble, sightengine. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_explicit_content",
              "description": "Explicit Content Detection detects adult only content in images, that is generally inappropriate for people under the age of 18 and includes nudity, sexual activity, pornography, violence, gore content, etc. (type of files allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, google, microsoft, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_compare",
              "description": "Compare two faces and decide whether they are from the same person. The API expects 2 images, reference and query, where the former is the ground truth (e.g. user's official ID) and the latter is the validation image (e.g. a selfie). File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file1": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "file2": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, base64, facepp. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file1",
                  "file2"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_detection",
              "description": "Face Detection is a computer technology being used in a variety of applications that identifies human faces in digital images with different attributes like landmarks, sentiments and physical attire (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_recognition",
              "description": "Recognizing a face in an image is a more advanced feature than just detecting the face in the image. It allows the user to search for the detected face from a database of existing images and extract the faces that are most similar to the face displayed in the query image. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "collection_id": {
                    "description": "Id of one of your collections. Make one with manage_collections (action='create', then add_item for each file to search against); action='list' shows the ones you have. 'model' must be the collection's provider.",
                    "type": "string"
                  },
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "collection_id",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_generation",
              "description": "Image Generation is an advanced feature that generates compelling images based on a given text prompt. It can easily produce high-quality and original images in a matter of seconds, without the need for specialized design skills or software File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "mask": {
                    "description": "Optional inpainting mask. Must be paired with at least one reference image (otherwise the request returns 422). Support varies by model; models that do not accept a mask surface the error as status=\"fail\" with a provider message in the response body. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: bytedance, bytedance/seedream-4-0-250828, bytedance/seedream-4-5-251128, bytedance/seedream-5-0-260128, google, google/gemini-2.5-flash-image, google/gemini-3-pro-image-preview, infomaniak/flux, ionos/black-forest-labs/FLUX.1-schnell, ionos/black-forest-labs/FLUX.2-klein-4B, leonardo, leonardo/AlbedoBase XL, leonardo/Leonardo Anime XL, leonardo/Leonardo Diffusion XL, leonardo/Leonardo Kino XL, leonardo/Leonardo Lightning XL, leonardo/Leonardo Phoenix, leonardo/Leonardo Vision XL, leonardo/SDXL 0.9, minimax, minimax/image-01, openai, openai/gpt-image-1, openai/gpt-image-1-mini, openai/gpt-image-1.5, openai/gpt-image-2, ovhcloud/stable-diffusion-xl-base-v10, pruna/p-image, pruna/p-image-edit, pruna/p-image-ideogram, pruna/p-image-ideogram-low, pruna/p-image-ideogram-medium, pruna/p-image-ideogram-very-high, pruna/p-image-ideogram-very-low, replicate, replicate/anime-style, replicate/classic, replicate/vintedois-diffusion, stabilityai, stabilityai/stable-diffusion-xl-1024-v1-0. Call list_models for pricing.",
                    "type": "string"
                  },
                  "num_images": {
                    "default": 1,
                    "description": "Number of images to generate",
                    "maximum": 10,
                    "minimum": 1,
                    "type": "integer"
                  },
                  "reference_images": {
                    "description": "Optional reference images. Plain file IDs/URLs are treated as ReferenceImage with kind=None. Support and per-model limits vary by model; models that do not accept reference images surface the error as status=\"fail\" with a provider message in the response body.",
                    "items": {},
                    "maxItems": 64,
                    "type": "array"
                  },
                  "resolution": {
                    "description": "Image resolution as a named size (e.g. '1024x1024'). Optional: providers may also accept native sizing knobs (width/height, aspect_ratio, image_size tier, etc.) in the top-level `provider_params` request field, next to `input` rather than inside it, in which case `provider_params` takes precedence.",
                    "pattern": "^\\d+x\\d+$",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text prompt for image generation",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_logo_detection",
              "description": "Logo Detection is a powerful technology that enables the automatic identification and recognition of popular logos within an image. It provides accurate and efficient detection of known (and less known) brand logos. It's a valuable tool for a variety of industries, including advertising, retail, and e-commerce. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai, api4ai/v1, api4ai/v2, google, microsoft, openai, openai/gpt-4-turbo, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_object_detection",
              "description": "Object Detection is a computer vision technique that allows users to identify and locate (with bounding boxes) objects in an image. The detected objects can be animals, people, electronics, vehicles etc. (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, microsoft, sentisight. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr",
              "description": "Optical Character Recognition or Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text. The image can be a scanned document or a photo of a license plate, a road sign or anything else that contains text (type of files allowed: jpg, jpeg, png, tiff) . File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, ionos, ionos/lightonai/LightOnOCR-2-1B, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest, sentisight. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_async",
              "description": "OCR or Optical Character Recognition is also referred to as text recognition or text extraction. It allows users to extract text data from PDFs with multiple pages. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_financial_parser",
              "description": "Financial Parser API is a powerful and versatile tool designed to streamline your financial data extraction process. This cutting-edge API combines Optical Character Recognition (OCR) technology with advanced parsing capabilities to seamlessly extract and organize relevant information from invoices and receipts. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "document_type": {
                    "default": "invoice",
                    "description": "Specify the type of your document. Can be set to 'auto-detect' for automatic detection if the provider supports it.",
                    "enum": [
                      "auto-detect",
                      "invoice",
                      "receipt"
                    ],
                    "type": "string"
                  },
                  "file": {
                    "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, eagledoc, extracta, google, klippa, microsoft, mindee, openai, openai/gpt-4o, tabscanner, veryfi. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_identity_parser",
              "description": "ID Document parsing technology allows users to automatically extract information from an ID Document such as passport, ID card, driving license and more. This API is ideal for developers looking to create applications that require identity verification or access control. It extracts information like name, date of birth, nationality, age and more. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, klippa, microsoft, mindee, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_resume_parser",
              "description": "Resume Parser enables users to extract various information from resumes (curriculum vitae, CV) that could be in a variety of formats and returns structured data (name, job list, education, skills) to automate their processing. (type of files allowed: pdf, jpg, jpeg, png) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, extracta, klippa, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_tables",
              "description": "OCR Table (Optical Character Recognition for tabular documents)  allows users to analyze documents containing tables and returns a structured representation of the detected tables in the form of a Json object that can be converted to a CSV. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, google, microsoft. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_ai_detection",
              "description": "The AI Detection API is a tool designed to determine whether a given text was generated by an artificial intelligence chatbot, or a Language Model (LLM).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: sapling, winstonai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for AI detection, at least 300 characters long. Shorter texts carry too little signal to be scored reliably.",
                    "minLength": 300,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_anonymization",
              "description": "The personally identifiable information (PII) detection feature can identify and redact sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Removing these personally identifiable information helps with the Anonymization of a text and privacy protection.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, limina, microsoft. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to detect personal information in",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_moderation",
              "description": "Text moderation scans text for offensive, sexually explicit or suggestive content, it also checks if there is any content of self-harm, violence, racist or hate speech.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: google, microsoft, openai, openai/text-moderation-007, openai/text-moderation-latest, openai/text-moderation-stable, ovhcloud/Qwen3Guard-Gen-0.6B, ovhcloud/Qwen3Guard-Gen-8B. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to moderate",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_named_entity_recognition",
              "description": "Named Entity Recognition (also called entity identification or extraction) is an information extraction technique that automatically identifies named entities in a text and classifies them into predefined categories such as dates, persons names, company names, dates, products etc.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, microsoft, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for named entities",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_plagia_detection",
              "description": "The Plagiarism Detection API is a tool designed to scan a content string for plagiarism using a plagiarism detection module",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: winstonai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text content on which plagiarism detection will be run",
                    "minLength": 1,
                    "type": "string"
                  },
                  "title": {
                    "description": "Content title",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_spell_check",
              "description": "Spell Check analyzes the inputted text by comparing it to a dictionary of correctly spelled words to identify and highlight any spelling errors or grammatical mistakes.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: prowritingaid, sapling. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to be spell-checked",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_topic_extraction",
              "description": "Topic analysis is a Natural Language Processing (NLP) technique that allows us to automatically extract meaning from text by identifying recurrent themes or topics.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: google, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for topics",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "translation_automatic_translation",
              "description": "Automatic translation or machine translation (MT) is the process of automatically translating a text from one language to another language. The aim of it is to enable people to communicate and access information in different languages, without the need for a human translator.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, deepl, google, microsoft, modernmt, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "source_language": {
                    "description": "Source language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "target_language": {
                    "description": "Target language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to translate",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text",
                  "target_language"
                ],
                "type": "object"
              }
            },
            {
              "name": "translation_document_translation",
              "description": "Document Translation API translates whole documents in supported languages and various file formats (like pdf or doc) while keeping their structure intact. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Document file ID from /v3/upload or direct file URL (PDF, DOCX, PPTX) Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/vnd.openxmlformats-officedocument.presentationml.presentation.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepl, google. Call list_models for pricing.",
                    "type": "string"
                  },
                  "source_language": {
                    "description": "Source language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "target_language": {
                    "description": "Target language code",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file",
                  "target_language"
                ],
                "type": "object"
              }
            },
            {
              "name": "video_deepfake_detection",
              "description": "Detect deepfake and synthetically manipulated video. Returns an overall deepfake score and prediction, along with per-frame scores when the provider supplies them. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Video file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "video_generation",
              "description": "The Video Generation API enables easy creation of high-quality videos from text,and images, perfect for marketing, education, and more—all through one integration. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "dimension": {
                    "default": "1280x720",
                    "description": "Video resolution in 'widthxheight' format (e.g., '1280x720')",
                    "pattern": "^\\d+x\\d+$",
                    "type": "string"
                  },
                  "duration": {
                    "description": "Length of the generated video in seconds. Omit to use the model's default duration.",
                    "maximum": 120,
                    "minimum": 1,
                    "type": "integer"
                  },
                  "file": {
                    "description": "Initial keyframe image (JPEG or PNG) file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/jpeg, image/png.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: bytedance, bytedance/dreamina-seedance-2-0-260128, bytedance/dreamina-seedance-2-0-fast-260128, bytedance/dreamina-seedance-2-0-mini-260615, bytedance/dreamina-seedance-2-5-260628, bytedance/seedance-1-0-pro-250528, bytedance/seedance-1-0-pro-fast-251015, bytedance/seedance-1-5-pro-251215, minimax, minimax/MiniMax-Hailuo-02, minimax/MiniMax-Hailuo-2.3, minimax/S2V-01, minimax/T2V/I2V-01-Director, openai, openai/sora-2, openai/sora-2-pro, pixverse, pixverse/c1, pixverse/v5, pixverse/v5.5, pixverse/v6, pruna, pruna/p-video, pruna/p-video-2, pruna/p-video-2-pro, pruna/p-video-2-pro-cost, pruna/p-video-2-pro-quality, pruna/p-video-animate, pruna/p-video-avatar, pruna/p-video-edit, xai/grok-imagine-video-1.5, xai/grok-imagine-video-1.5-lite. Call list_models for pricing.",
                    "type": "string"
                  },
                  "seed": {
                    "description": "Random seed for generation reproducibility (0 to 2,147,483,646). Omit for varied output.",
                    "maximum": 2147483646,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "text": {
                    "description": "Text prompt describing the content and style of the video to generate",
                    "minLength": 1,
                    "type": "string"
                  },
                  "video": {
                    "description": "Source video to edit, for models that edit a video (their `requires_video` is true in /v3/info). The output keeps the source's length, which is what is billed, so `duration` and `dimension` do not apply to them. Other models refuse it. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_batch_scrape",
              "description": "Scrape many URLs in one request and return each page's content. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.",
                    "type": "string"
                  },
                  "urls": {
                    "description": "Explicit list of URLs to scrape (async job)",
                    "items": {
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "urls"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_crawl",
              "description": "Crawl a site from a starting URL and return the content of its pages. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "Root URL to crawl (async job)",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_map",
              "description": "Discover and return the list of URLs on a site (a sitemap-style link map).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "Root URL to map (discover its links)",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_research",
              "description": "Run deep, multi-step web research on a query and return a synthesized answer with sources. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, linkup, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "prompt": {
                    "description": "Natural-language research task for the agent",
                    "minLength": 1,
                    "type": "string"
                  },
                  "reasoning_depth": {
                    "default": "L",
                    "description": "Research reasoning-effort tier (billed per tier; priced pre-call)",
                    "enum": [
                      "S",
                      "M",
                      "L",
                      "XL"
                    ],
                    "type": "string"
                  },
                  "schema": {
                    "description": "JSON schema describing the structured output",
                    "type": "object"
                  }
                },
                "required": [
                  "model",
                  "prompt"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_scraping",
              "description": "Fetch a single URL and return its clean content as markdown, text, or HTML, with optional JavaScript rendering.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "URL of the web page to scrape",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_search",
              "description": "Search the web for a query and return ranked results (title, URL, and a snippet or the page content).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "depth": {
                    "default": "standard",
                    "description": "Search depth tier. `deep` is refused with a 400 on deepseek, perplexityai and zai, which run one tier only.",
                    "enum": [
                      "standard",
                      "deep"
                    ],
                    "type": "string"
                  },
                  "max_results": {
                    "description": "Max number of search results to return",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, perplexityai, tavily, zai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "query": {
                    "description": "The web search query",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "query"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_structured_extraction",
              "description": "Extract structured data from one or more web pages against a schema or prompt. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.",
                    "type": "string"
                  },
                  "prompt": {
                    "description": "Natural-language description of what to extract",
                    "type": "string"
                  },
                  "schema": {
                    "description": "JSON schema describing the structured output",
                    "type": "object"
                  },
                  "urls": {
                    "description": "URLs to extract structured data from (async job)",
                    "items": {
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "urls"
                ],
                "type": "object"
              }
            }
          ],
          "schemaTokens": 10725,
          "changedAt": "2026-11-07T01:44:01.27972989Z",
          "check": {
            "checker": "anchor-check/1.0",
            "totalTokens": 10725,
            "counts": {
              "error": 0,
              "note": 1,
              "warn": 49
            },
            "findings": [
              {
                "rule": "TC11",
                "severity": "warn",
                "tool": "manage_collections",
                "message": "1 parameter without a description: action",
                "fix": "Describe each one: format, units, an example, and what happens when it's left out."
              },
              {
                "rule": "TC12",
                "severity": "warn",
                "tool": "image_generation",
                "message": "no type for reference_images[]",
                "fix": "Give every parameter a type (or an enum)."
              },
              {
                "rule": "TC13",
                "severity": "warn",
                "tool": "web_research",
                "message": "schema (object with no properties)",
                "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
              },
              {
                "rule": "TC13",
                "severity": "warn",
                "tool": "web_structured_extraction",
                "message": "schema (object with no properties)",
                "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
              },
              {
                "rule": "TC14",
                "severity": "warn",
                "tool": "image_face_recognition",
                "message": "allowed values are in the description, not an enum: collection_id",
                "fix": "Move them into enum."
              },
              {
                "rule": "TC14",
                "severity": "warn",
                "tool": "image_generation",
                "message": "allowed values are in the description, not an enum: resolution",
                "fix": "Move them into enum."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "audio_speech_to_text",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "audio_tts",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "check_job",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_ai_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_anonymization",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_background_removal",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_deepfake_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_explicit_content",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_compare",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_recognition",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_generation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_logo_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_object_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "list_models",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "list_voices",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "manage_collections",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_async",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_financial_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_identity_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_resume_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_tables",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_ai_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_anonymization",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_moderation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_named_entity_recognition",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_plagia_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_spell_check",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_topic_extraction",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "translation_automatic_translation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "translation_document_translation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "upload_file",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "video_deepfake_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "video_generation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_batch_scrape",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_crawl",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_map",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_research",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_scraping",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_search",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_structured_extraction",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC23",
                "severity": "warn",
                "message": "42 tools",
                "fix": "Offer a smaller default toolset and let clients opt into the rest."
              },
              {
                "rule": "TC24",
                "severity": "note",
                "message": "38 of 42 tools have no outputSchema",
                "fix": "Declare outputSchema for tools that return structured data, and return structuredContent that matches it."
              }
            ]
          }
        },
        "updatedAt": "2026-11-07T19:22:04.810042763Z"
      }
    },
    "answer": "Eden AI scores 59.9 (C) on agent readiness against SiliconFlow's 42.9 (E), and leads in 5 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.",
    "b": {
      "slug": "siliconflow",
      "name": "SiliconFlow",
      "vendor": "SiliconFlow Labs Pte. Ltd.",
      "vendorUrl": "https://www.siliconflow.com",
      "kind": "model",
      "category": "inference",
      "summary": "SiliconFlow is a hosted inference API for open-weight models, covering chat, vision, embeddings, reranking, image, video and speech. It answers OpenAI-style and Anthropic-style calls at api.siliconflow.com with a Bearer key.",
      "url": "https://www.anchorterminal.com/tools/siliconflow",
      "markdownUrl": "https://www.anchorterminal.com/tools/siliconflow.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/siliconflow.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/siliconflow.json",
      "dns": "siliconflow.grade.anchorterminal.com",
      "license": "Proprietary service under the SiliconFlow Terms of Use",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.siliconflow.com/v1",
      "packages": [],
      "auth": "api-key",
      "authNotes": "Self-serve Bearer key from the console at https://cloud.siliconflow.com/account/ak after a browser sign-up with a Google or GitHub account. The Anthropic-style `/messages` route also takes the key in `x-api-key`. No scopes, expiry or per-key limits are documented, and rate limits apply to the account, not the key. The error page says some models answer 403 until real-name authentication is done.",
      "pricing": "usage",
      "pricingNotes": "Pay per token, image, video or byte of speech text, with $1 in free credits for a new account. Whether a card is needed to claim the credit was not established. DeepSeek-V4.1-Flash costs $0.15 in, $0.003 cached and $0.60 out per 1M tokens. The FAQ says monthly spending limits can be set in the dashboard (https://www.siliconflow.com/pricing, checked 2026-10-09).",
      "priceSummary": "from $0.15 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI file or the pricing page (checked 2026-10-09).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-09"
      },
      "docsUrl": "https://docs.siliconflow.com/en/userguide/quickstart",
      "rateLimitsUrl": "https://docs.siliconflow.com/cn/userguide/rate-limits/rate-limit-and-upgradation",
      "llmsTxt": "https://docs.siliconflow.com/llms.txt",
      "openapi": "https://docs.siliconflow.com/cn/api-reference/openapi.yaml",
      "capabilities": [
        "inference.llm",
        "inference.open-weights",
        "embed.text",
        "rerank",
        "image.generate",
        "video.generate",
        "speech.tts",
        "speech.stt"
      ],
      "tags": [
        "hosted",
        "model",
        "open-weights",
        "usage-based",
        "free-credit",
        "openapi",
        "llms-txt",
        "openai-compatible",
        "anthropic-compatible",
        "singapore"
      ],
      "lastRelease": "2026-09-14",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 42.9,
        "grade": "E",
        "agentReady": false,
        "rank": 1266,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 39,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 60,
          "maintenance": 37,
          "payments": 35,
          "reliability": 33,
          "schema": 65,
          "security": 39,
          "transparency": 52
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-05"
        },
        "negative": -3,
        "negativeNotes": [
          "2025-12-31 to 2026-06-11. SiliconFlow's release notes carry six model removal entries dated the day the models were removed, with no earlier entry announcing them, and on 11 June 2026 all traffic for `zai-org/GLM-5` and `moonshotai/Kimi-K2.5` was routed to successor models in an entry of the same date. Requests naming those models stopped working or changed model with notice only on the day. Read at the floor and folded into one term, as together-inference's and fireworks-inference's same-day serverless removals were, -3 (https://docs.siliconflow.com/en/release-notes/overview, per the 9 October reading)."
        ],
        "verdict": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.",
        "bestFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.",
        "strengths": [
          "Per-token, per-image and per-video prices are public for every listed model, such as DeepSeek-V4.1-Flash at $0.15 in and $0.60 out per 1M tokens",
          "One Bearer key reaches 22 operations in a public OpenAPI 3.0 file, with OpenAI-style `/chat/completions` and Anthropic-style `/messages`",
          "`llms.txt` and a Markdown copy of every docs page, in English and Chinese",
          "Rate limits are published by spend tier, from 1,000 requests and 40,000 tokens a minute at L0 to 10,000 and 2,000,000 at L5",
          "The terms say SiliconFlow will not access Interaction Data, has no obligation to store it, and uses it only to supply the service"
        ],
        "weaknesses": [
          "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment",
          "Release notes stop at 11 June 2026. Six notices from December 2025 to June 2026 give a removal date equal to the notice date",
          "The Terms of Use of 9 September 2026 forbid use for any commercial purposes, scraping tools and benchmarking. This matters before any probe is run",
          "The OpenAPI model list and the function calling guide name models already removed, and omit every model added since July 2026",
          "No security.txt, disclosure policy, certification, DPA or sub-processor list was found, and no official SDK is published"
        ],
        "agentNotes": [
          "Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token",
          "Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models",
          "Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models",
          "Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length",
          "Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "E",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 42.9
          }
        ],
        "editorialScores": {
          "ergonomics": 60,
          "maintenance": 37,
          "payments": 35,
          "reliability": 33,
          "schema": 65,
          "security": 39,
          "transparency": 34
        },
        "provenanceScore": 70,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-05",
            "maintenance": "2026-11-05",
            "payments": "2026-11-05",
            "reliability": "2026-11-05",
            "schema": "2026-11-05",
            "security": "2026-11-05",
            "transparency": "2026-11-05"
          },
          "last": "2026-11-05",
          "lastMoved": "2026-11-05",
          "oldest": "2026-11-05",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install --upgrade openai",
        "http": "curl --request POST \\\n  --url https://api.siliconflow.com/v1/chat/completions \\\n  --header 'authorization: Bearer $SILICONFLOW_API_KEY' \\\n  --header 'content-type: application/json' \\\n  --data '{\"model\":\"deepseek-ai/DeepSeek-V4.1-Flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"max_tokens\":128}'",
        "claudeCode": "export ANTHROPIC_BASE_URL=\"https://api.siliconflow.com/\"\nexport ANTHROPIC_MODEL=\"your-preferred-model\"\nexport ANTHROPIC_API_KEY=\"sk-your-api-key-here\""
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/siliconflow"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Z-Image-Turbo, one image",
          "unit": "image",
          "usd": 0.005
        },
        {
          "item": "FLUX.1-dev, one image",
          "unit": "image",
          "usd": 0.014
        },
        {
          "item": "FLUX 1.1 [pro], one image",
          "unit": "image",
          "usd": 0.04
        },
        {
          "item": "Wan2.2-T2V-A14B, one video",
          "unit": "call",
          "usd": 0.29,
          "note": "Priced per video generated"
        }
      ],
      "provenance": {
        "legalEntity": "SiliconFlow Labs Pte. Ltd.",
        "domain": "siliconflow.com",
        "domainRegistered": "2019-02-14",
        "endpointOnVendorDomain": true,
        "terms": "https://docs.siliconflow.com/en/legals/terms-of-service",
        "privacy": "https://docs.siliconflow.com/en/legals/privacy-policy",
        "statusPage": "",
        "changelog": "https://docs.siliconflow.com/en/release-notes/overview",
        "securityTxt": "none",
        "checked": "2026-11-05",
        "notes": [
          "The Terms of Use, updated 9 September 2026, name SILICONFLOW LABS PTE. LTD., apply Singapore law and set SIAC arbitration in Singapore. They govern the platform in its web, API and mobile versions, and no separate API agreement was found.",
          "The Privacy Policy, updated 9 September 2026, names the same entity and cites Singapore's Personal Data Protection Act 2012. It keeps square brackets around several values, such as [Stripe] and [Google and GitHub].",
          "No status page is linked from the site, the docs index or the pages read.",
          "https://www.siliconflow.com/.well-known/security.txt answered 404.",
          "The API answers at api.siliconflow.com, the docs at docs.siliconflow.com and the console at cloud.siliconflow.com. The terms point users in mainland China to siliconflow.cn.",
          "No SLA, DPA or sub-processor list was found.",
          "The Terms of Use (updated 9 September 2026) clause 3.4(i) bar any manual or automated software, including spiders, robots, scrapers and crawlers, to scrape, collect or download information from the Platform or Services, which they define to include the web, API and mobile versions (read 5 November 2026).",
          "The domain registration date was recorded from an RDAP lookup on 9 October 2026, a source this check doesn't use. It wasn't re-read."
        ],
        "score": 70
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/siliconflow.json",
      "live": {
        "slug": "siliconflow",
        "probe": {
          "target": "https://api.siliconflow.com/v1",
          "method": "get",
          "lastAt": "2026-11-07T19:22:33.096265082Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 359,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 99.99,
          "p50ms24h": 276,
          "p95ms24h": 377,
          "samples24h": 238,
          "samples30d": 7215,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 85,
              "ok": 85
            },
            {
              "date": "2026-10-10",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-11",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-12",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-15",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-16",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-17",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-18",
              "probes": 256,
              "ok": 256
            },
            {
              "date": "2026-10-19",
              "probes": 255,
              "ok": 255
            },
            {
              "date": "2026-10-20",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-21",
              "probes": 253,
              "ok": 252
            },
            {
              "date": "2026-10-22",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-23",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-24",
              "probes": 251,
              "ok": 251
            },
            {
              "date": "2026-10-25",
              "probes": 250,
              "ok": 250
            },
            {
              "date": "2026-10-26",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-27",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-28",
              "probes": 250,
              "ok": 250
            },
            {
              "date": "2026-10-29",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-30",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-31",
              "probes": 251,
              "ok": 251
            },
            {
              "date": "2026-11-01",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-11-02",
              "probes": 250,
              "ok": 250
            },
            {
              "date": "2026-11-03",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-11-04",
              "probes": 246,
              "ok": 246
            },
            {
              "date": "2026-11-05",
              "probes": 185,
              "ok": 185
            },
            {
              "date": "2026-11-06",
              "probes": 241,
              "ok": 241
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "securityTxt": {
          "url": "https://siliconflow.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-07T16:01:29.327038169Z"
        },
        "llmsTxt": {
          "url": "https://docs.siliconflow.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:33:55.35975587Z"
        },
        "domain": {
          "domain": "siliconflow.com",
          "registered": "2019-02-14",
          "source": "https://rdap.verisign.com/com/v1/domain/siliconflow.com",
          "checkedAt": "2026-11-01T14:18:54.160809284Z"
        },
        "pages": [
          {
            "url": "https://docs.siliconflow.com/en/release-notes/overview",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:02.877282346Z",
            "changedAt": "2026-10-26T03:15:35.683654862Z",
            "fingerprint": "174b36f1f0c8"
          },
          {
            "url": "https://www.siliconflow.com/pricing",
            "kind": "pricing",
            "status": 304,
            "checkedAt": "2026-11-07T14:34:38.076372647Z",
            "changedAt": "2026-10-22T01:36:57.039692841Z",
            "fingerprint": "e1314294f4a8"
          },
          {
            "url": "https://docs.siliconflow.com/en/legals/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-07T14:07:58.655668132Z",
            "changedAt": "2026-10-26T03:15:31.436126122Z",
            "fingerprint": "6533065904d9"
          },
          {
            "url": "https://docs.siliconflow.com/en/legals/terms-of-service",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:00.852123613Z",
            "changedAt": "2026-10-26T03:15:33.589043532Z",
            "fingerprint": "9b70022b01e3"
          }
        ],
        "updatedAt": "2026-11-07T19:22:33.096265082Z"
      }
    },
    "edges": [
      {
        "by": 43,
        "category": "security",
        "leads": "eden-ai",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.",
          "b": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Bearer keys created in the console. No scopes, expiry, per-key limits or rotation are documented, and deletion of a key was not confirmed because the console was not read (15 of 30). The terms say Interaction Data is used only to supply the service and is not used or disclosed without authorisation. No statement on model training was found (12 of 20). The terms say there is no obligation to store Interaction Data. No retention period or zero-retention option is stated, and clause 5.11 allows communications to be recorded and passed to the authorities (6 of 15). The release note of 26 March 2026 describes usage and cost breakdowns and invoice export, and the pricing FAQ says monthly spending limits can be set. No audit log was found (6 of 15). No security.txt (404), disclosure policy, bug bounty or named certification was found on the pages read. The product introduction says the service complies with industry standards and names none (0 of 20). 15+12+6+6+0 = 39."
        },
        "scores": {
          "a": 82,
          "b": 39
        }
      },
      {
        "by": 21,
        "category": "maintenance",
        "leads": "eden-ai",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.",
          "b": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Model reading, per the 9 October check, not re-read on 5 November. Hy4-preview is listed as released on 14 September 2026, 52 days before this check, and no later model or API change was recorded; blog post dates record no API change (20). No notice period is stated. Six removal notices from 31 December 2025 to 11 June 2026 are dated the day of removal, and two in March 2026 gave six and seven days (2 of 12). The release notes record about 60 model ids removed in ten notices over the last twelve months (2 of 8). The release notes stop at 11 June 2026 while nine chat models were added afterwards. Support is by email and Discord (6 of 15). Replies in the support channels were not examined (2 of 10). No official SDK. The `langchain-siliconflow` repository in the vendor's GitHub organisation was last changed on 12 December 2025 (version 0.2.3), confirmed from a clone on 5 November (3 of 15). The API description and two guides are out of date (2 of 10). 20+2+2+6+2+3+2 = 37."
        },
        "scores": {
          "a": 58,
          "b": 37
        }
      },
      {
        "by": 16,
        "category": "schema",
        "leads": "eden-ai",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.",
          "b": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Public OpenAPI 3.0 file with 22 operations and 102 schemas, linked from `llms.txt` under the Chinese path only. Its chat model enum of 71 ids includes removed models and omits every model added since July 2026 (19 of 25). `llms.txt` and a Markdown copy of each docs page (10). Guides for function calling, JSON mode, reasoning, prefix and FIM completion. The function calling guide lists only models the release notes show as removed, and its examples use DeepSeek-V2.5 (10 of 20). Typed parameters with 104 enums and required fields. `response_format` is typed as a bare string with an example (10 of 15). Curl and Python examples, an error page with seven HTTP codes and one body code, and 400, 401, 404, 429, 503 and 504 responses in the file (9 of 15). The file's version reads 1.0.0. The release notes are dated, stop at 11 June 2026 and since March 2026 record only model removals (7 of 15). 19+10+10+10+9+7 = 65."
        },
        "scores": {
          "a": 81,
          "b": 65
        }
      },
      {
        "by": 15,
        "category": "ergonomics",
        "leads": "eden-ai",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.",
          "b": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI-style `tools` with up to 128 functions, and each model page says whether Tools are supported. No `tool_choice` field is in the chat schema and the guide is out of date (12 of 20). `response_format` of `json_object`. The DeepSeek-V4.1-Flash page says Structured Outputs are not supported (7 of 15). Cached input prices are published per model. No caching guide was found (8 of 15). Context listed as 1049K tokens on eleven chat models on the home page, with output up to 393K (14 of 15). `/files` and `/batches` are in the OpenAPI file for chat completions only, with no guide in the English index, no batch price and a window description that contradicts itself (5 of 10). No official SDK. The OpenAI and Anthropic clients work with a changed base URL (6 of 10). Errors carry an HTTP status, a numeric code and a message. No list of codes was found (8 of 15). 12+7+8+14+5+6+8 = 60."
        },
        "scores": {
          "a": 75,
          "b": 60
        }
      },
      {
        "by": 5,
        "category": "payments",
        "leads": "siliconflow",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.",
          "b": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. No machine payment protocol (0). Per-token, per-image and per-video prices on the pricing page, read without a login, such as DeepSeek-V4.1-Flash at $0.15 in and $0.60 out per 1M tokens (20). $1 in free credits for a new account. Whether a card is needed was not established, so this line takes 15 of 20. A person signs up in a browser with a Google or GitHub account, and no key API was found (0). 0+20+15+0 = 35."
        },
        "scores": {
          "a": 30,
          "b": 35
        }
      }
    ],
    "facts": [
      {
        "a": "Model router",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Eden AI SAS",
        "b": "SiliconFlow Labs Pte. Ltd.",
        "name": "Vendor"
      },
      {
        "a": "https://mcp.edenai.run/mcp",
        "b": "https://api.siliconflow.com/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, Streamable HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "none",
        "b": "Proprietary service under the SiliconFlow Terms of Use",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-11-05",
        "b": "2026-09-14",
        "name": "Last release"
      },
      {
        "a": "2026-10-22",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "2026-10-22",
        "b": "no date given",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Eden AI scores 59.9 (C) on agent readiness against SiliconFlow's 42.9 (E), and leads in 5 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Eden AI or SiliconFlow?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Eden AI and SiliconFlow need an API key?"
      },
      {
        "answer": "Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and SiliconFlow at https://api.siliconflow.com/v1.",
        "question": "Can an agent call Eden AI and SiliconFlow without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 81 against 65",
          "Agent ergonomics, 75 against 60",
          "Security \u0026 auth, 82 against 39",
          "Maintenance \u0026 community, 58 against 37"
        ],
        "also": [
          "No incidents deducted, where SiliconFlow loses 3 points for them"
        ],
        "goodFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.",
        "slug": "eden-ai",
        "watchFor": "No public status page, incident history or SLA found"
      },
      {
        "aheadOn": [
          "Payments \u0026 pricing, 35 against 30"
        ],
        "also": null,
        "goodFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.",
        "slug": "siliconflow",
        "watchFor": "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment"
      }
    ],
    "history": {
      "eden-ai": null,
      "siliconflow": [
        {
          "causes": [
            "correction",
            "time"
          ],
          "date": "2026-11-05",
          "delta": -3.9,
          "from": 46.8,
          "fromGrade": "D",
          "to": 42.9,
          "toGrade": "E"
        },
        {
          "causes": [
            "correction"
          ],
          "date": "2026-10-28",
          "delta": -0.2,
          "from": 47,
          "fromGrade": "D",
          "to": 46.8,
          "toGrade": "D"
        },
        {
          "causes": [
            "method"
          ],
          "date": "2026-10-27",
          "delta": 0.3,
          "from": 46.7,
          "fromGrade": "D",
          "to": 47,
          "toGrade": "D"
        }
      ]
    },
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.json",
        "title": "Amazon Bedrock vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.json",
        "title": "Amazon Bedrock vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.json",
        "title": "Claude API vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.json",
        "title": "Claude API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-siliconflow.json",
        "title": "Antseed vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.json",
        "title": "Azure OpenAI in Foundry Models vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.json",
        "title": "Azure OpenAI in Foundry Models vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.json",
        "title": "BlockRun.AI vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.json",
        "title": "BlockRun.AI vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.json",
        "title": "Cerebras Inference vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.json",
        "title": "Cerebras Inference vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai.json",
        "title": "Cloudflare AI Gateway vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.json",
        "title": "Cloudflare AI Gateway vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai.json",
        "title": "Cloudflare Workers AI vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.json",
        "title": "Cloudflare Workers AI vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai.json",
        "title": "Cohere Chat API (Command models) vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.json",
        "title": "Cohere Chat API (Command models) vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai.json",
        "title": "DeepInfra vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.json",
        "title": "DeepInfra vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai.json",
        "title": "DeepSeek API vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.json",
        "title": "DeepSeek API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse.json",
        "title": "Eden AI vs Glimpse",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.json",
        "title": "Eden AI vs Fireworks AI Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api.json",
        "title": "Eden AI vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-groq.json",
        "title": "Eden AI vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.json",
        "title": "Eden AI vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.json",
        "title": "Eden AI vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.json",
        "title": "Eden AI vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api.json",
        "title": "Eden AI vs MiniMax API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api.json",
        "title": "Eden AI vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.json",
        "title": "Eden AI vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl.json",
        "title": "Eden AI vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.json",
        "title": "Eden AI vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json",
        "title": "Eden AI vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference.json",
        "title": "Eden AI vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.json",
        "title": "Eden AI vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.json",
        "title": "Eden AI vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.json",
        "title": "Eden AI vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.json",
        "title": "Eden AI vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash.json",
        "title": "Eden AI vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.json",
        "title": "Eden AI vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.json",
        "title": "Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.json",
        "title": "Eden AI vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow.json",
        "title": "Glimpse vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.json",
        "title": "Fireworks AI Inference vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.json",
        "title": "Gemini Developer API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-siliconflow.json",
        "title": "GroqCloud vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/groq-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow.json",
        "title": "Hugging Face Inference Providers vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow.json",
        "title": "Inkling 2 Small vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.json",
        "title": "Jais 3 vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json",
        "title": "Meta Model API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow.json",
        "title": "MiniMax API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.json",
        "title": "Mistral AI API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json",
        "title": "Muse Spark Open vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json",
        "title": "Novita AI vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json",
        "title": "OpenAI API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.json",
        "title": "OpenRouter vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.json",
        "title": "Prism Inference vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow.json",
        "title": "Router.com (Ramp Router) vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.json",
        "title": "Beam 1.0 vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow.json",
        "title": "RouterPlus vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.json",
        "title": "SambaCloud vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart.json",
        "title": "SiliconFlow vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.json",
        "title": "SiliconFlow vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-swe-2-flash.json",
        "title": "SiliconFlow vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub.json",
        "title": "SiliconFlow vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.json",
        "title": "SiliconFlow vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway.json",
        "title": "SiliconFlow vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.json",
        "title": "SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api.json",
        "title": "SiliconFlow vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai.json",
        "title": "Antseed vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.json",
        "title": "Eden AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm.json",
        "title": "Eden AI vs LiteLLM",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter.json",
        "title": "Eden AI vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router.json",
        "title": "Eden AI vs Router.com (Ramp Router)",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus.json",
        "title": "Eden AI vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub.json",
        "title": "Eden AI vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.json",
        "title": "Eden AI vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-siliconflow.json",
        "title": "Nemotron 3.5 Super VL vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-siliconflow"
      }
    ],
    "panel": null,
    "scores": [
      {
        "by": 0,
        "eden-ai": 33,
        "edge": "",
        "key": "reliability",
        "name": "Reliability",
        "siliconflow": 33,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 16,
        "eden-ai": 81,
        "edge": "eden-ai",
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "siliconflow": 65,
        "weight": 13
      },
      {
        "by": 15,
        "eden-ai": 75,
        "edge": "eden-ai",
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "siliconflow": 60,
        "weight": 13
      },
      {
        "by": 43,
        "eden-ai": 82,
        "edge": "eden-ai",
        "key": "security",
        "name": "Security \u0026 auth",
        "siliconflow": 39,
        "weight": 14
      },
      {
        "by": 5,
        "eden-ai": 30,
        "edge": "siliconflow",
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "siliconflow": 35,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 21,
        "eden-ai": 58,
        "edge": "eden-ai",
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "siliconflow": 37,
        "weight": 7
      },
      {
        "by": 3,
        "eden-ai": 55,
        "edge": "eden-ai",
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "siliconflow": 52,
        "weight": 7
      }
    ],
    "summary": "Eden AI scores 59.9 (C) on agent readiness against SiliconFlow's 42.9 (E), and leads in 5 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "eden-ai": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.",
      "siliconflow": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice."
    }
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  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow",
    "json": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.min.md"
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  "markdown": "Eden AI scores 59.9 (C) on agent readiness against SiliconFlow's 42.9 (E), and leads in 5 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing. Both do llm inference.\n\n- Eden AI: grade C, 59.9/100, rank #675 of 1510. Markdown https://www.anchorterminal.com/tools/eden-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n- SiliconFlow: grade E, 42.9/100, rank #1266 of 1510. Markdown https://www.anchorterminal.com/tools/siliconflow.md · JSON https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Eden AI (C)\n\nGood for: Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.\n\nAhead on:\n- Schema \u0026 documentation, 81 against 65\n- Agent ergonomics, 75 against 60\n- Security \u0026 auth, 82 against 39\n- Maintenance \u0026 community, 58 against 37\n\nAlso in its favour:\n- No incidents deducted, where SiliconFlow loses 3 points for them\n\nWatch for: No public status page, incident history or SLA found\n\n### SiliconFlow (E)\n\nGood for: Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.\n\nAhead on:\n- Payments \u0026 pricing, 35 against 30\n\nWatch for: No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment\n\n\n## Why the edge\n\n### Security \u0026 auth: Eden AI +43\n\n- Eden AI (82): Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.\n- SiliconFlow (39): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Bearer keys created in the console. No scopes, expiry, per-key limits or rotation are documented, and deletion of a key was not confirmed because the console was not read (15 of 30). The terms say Interaction Data is used only to supply the service and is not used or disclosed without authorisation. No statement on model training was found (12 of 20). The terms say there is no obligation to store Interaction Data. No retention period or zero-retention option is stated, and clause 5.11 allows communications to be recorded and passed to the authorities (6 of 15). The release note of 26 March 2026 describes usage and cost breakdowns and invoice export, and the pricing FAQ says monthly spending limits can be set. No audit log was found (6 of 15). No security.txt (404), disclosure policy, bug bounty or named certification was found on the pages read. The product introduction says the service complies with industry standards and names none (0 of 20). 15+12+6+6+0 = 39.\n\n### Maintenance \u0026 community: Eden AI +21\n\n- Eden AI (58): Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.\n- SiliconFlow (37): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Model reading, per the 9 October check, not re-read on 5 November. Hy4-preview is listed as released on 14 September 2026, 52 days before this check, and no later model or API change was recorded; blog post dates record no API change (20). No notice period is stated. Six removal notices from 31 December 2025 to 11 June 2026 are dated the day of removal, and two in March 2026 gave six and seven days (2 of 12). The release notes record about 60 model ids removed in ten notices over the last twelve months (2 of 8). The release notes stop at 11 June 2026 while nine chat models were added afterwards. Support is by email and Discord (6 of 15). Replies in the support channels were not examined (2 of 10). No official SDK. The `langchain-siliconflow` repository in the vendor's GitHub organisation was last changed on 12 December 2025 (version 0.2.3), confirmed from a clone on 5 November (3 of 15). The API description and two guides are out of date (2 of 10). 20+2+2+6+2+3+2 = 37.\n\n### Schema \u0026 documentation: Eden AI +16\n\n- Eden AI (81): Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.\n- SiliconFlow (65): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Public OpenAPI 3.0 file with 22 operations and 102 schemas, linked from `llms.txt` under the Chinese path only. Its chat model enum of 71 ids includes removed models and omits every model added since July 2026 (19 of 25). `llms.txt` and a Markdown copy of each docs page (10). Guides for function calling, JSON mode, reasoning, prefix and FIM completion. The function calling guide lists only models the release notes show as removed, and its examples use DeepSeek-V2.5 (10 of 20). Typed parameters with 104 enums and required fields. `response_format` is typed as a bare string with an example (10 of 15). Curl and Python examples, an error page with seven HTTP codes and one body code, and 400, 401, 404, 429, 503 and 504 responses in the file (9 of 15). The file's version reads 1.0.0. The release notes are dated, stop at 11 June 2026 and since March 2026 record only model removals (7 of 15). 19+10+10+10+9+7 = 65.\n\n### Agent ergonomics: Eden AI +15\n\n- Eden AI (75): Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.\n- SiliconFlow (60): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI-style `tools` with up to 128 functions, and each model page says whether Tools are supported. No `tool_choice` field is in the chat schema and the guide is out of date (12 of 20). `response_format` of `json_object`. The DeepSeek-V4.1-Flash page says Structured Outputs are not supported (7 of 15). Cached input prices are published per model. No caching guide was found (8 of 15). Context listed as 1049K tokens on eleven chat models on the home page, with output up to 393K (14 of 15). `/files` and `/batches` are in the OpenAPI file for chat completions only, with no guide in the English index, no batch price and a window description that contradicts itself (5 of 10). No official SDK. The OpenAI and Anthropic clients work with a changed base URL (6 of 10). Errors carry an HTTP status, a numeric code and a message. No list of codes was found (8 of 15). 12+7+8+14+5+6+8 = 60.\n\n### Payments \u0026 pricing: SiliconFlow +5\n\n- Eden AI (30): No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.\n- SiliconFlow (35): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. No machine payment protocol (0). Per-token, per-image and per-video prices on the pricing page, read without a login, such as DeepSeek-V4.1-Flash at $0.15 in and $0.60 out per 1M tokens (20). $1 in free credits for a new account. Whether a card is needed was not established, so this line takes 15 of 20. A person signs up in a browser with a Google or GitHub account, and no key API was found (0). 0+20+15+0 = 35.\n\n## Score by category\n\n| Category | Weight | Eden AI | SiliconFlow | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 33 | 33 | even |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 81 | 65 | Eden AI +16 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 60 | Eden AI +15 |\n| Security \u0026 auth | 14% (17.5 this run) | 82 | 39 | Eden AI +43 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 35 | SiliconFlow +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 58 | 37 | Eden AI +21 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 52 | Eden AI +3 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **59.9 · C** | **42.9 · E** | |\n\n## Facts side by side\n\n| Fact | Eden AI | SiliconFlow |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Eden AI SAS | SiliconFlow Labs Pte. Ltd. |\n| Hosted endpoint | `https://mcp.edenai.run/mcp` | `https://api.siliconflow.com/v1` |\n| Transports | HTTP, Streamable HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Proprietary service under the SiliconFlow Terms of Use |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-05 | 2026-09-14 |\n| Terms last updated | 2026-10-22 | no date given |\n| Privacy policy last updated | 2026-10-22 | no date given |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | not found in the text | yes |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Eden AI\n\nNo score change since it was listed.\n\n### SiliconFlow\n\n- -3.9 on 5 November 2026 (D to E): correction, time\n- -0.2 on 28 October 2026: correction\n- +0.3 on 27 October 2026: checklist\n\n## Verdicts\n\n**Eden AI.** Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.\n\n**SiliconFlow.** Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.\n\n## Before you call either\n\n### Eden AI\n\n1. Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them\n2. Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed\n3. Set max_tokens to 500 or more for reasoning models, or the answer can come back empty\n4. Pass a fallbacks list so a provider 429 or error retries inside one request\n5. Poll check_job for MCP tools marked long-running instead of calling them again\n\n### SiliconFlow\n\n1. Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token\n2. Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models\n3. Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models\n4. Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length\n5. Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash\n\n## Questions\n\n### Which is better for AI agents, Eden AI or SiliconFlow?\n\nEden AI scores 59.9 (C) on agent readiness against SiliconFlow's 42.9 (E), and leads in 5 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.\n\n### Do Eden AI and SiliconFlow need an API key?\n\nBoth need an API key.\n\n### Can an agent call Eden AI and SiliconFlow without installing anything?\n\nYes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and SiliconFlow at https://api.siliconflow.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.json, and with the fewest tokens: https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"eden-ai\", \"b\": \"siliconflow\"}`. From a terminal: `anchor compare eden-ai siliconflow`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/eden-ai.json and https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n\n## Other comparisons with Eden AI or SiliconFlow\n\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs SiliconFlow](https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.md)\n- [Claude API vs Eden AI](https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md)\n- [Claude API vs SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Antseed vs SiliconFlow](https://www.anchorterminal.com/compare/antseed-vs-siliconflow.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [Azure OpenAI in Foundry Models vs SiliconFlow](https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.md)\n- [BlockRun.AI vs Eden AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.md)\n- [BlockRun.AI vs SiliconFlow](https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.md)\n- [Cerebras Inference vs Eden AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.md)\n- [Cerebras Inference vs SiliconFlow](https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.md)\n- [Cloudflare AI Gateway vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai.md)\n- [Cloudflare AI Gateway vs SiliconFlow](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.md)\n- [Cloudflare Workers AI vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai.md)\n- [Cloudflare Workers AI vs SiliconFlow](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.md)\n- [Cohere Chat API (Command models) vs Eden AI](https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai.md)\n- [Cohere Chat API (Command models) vs SiliconFlow](https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.md)\n- [DeepInfra vs Eden AI](https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai.md)\n- [DeepInfra vs SiliconFlow](https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.md)\n- [DeepSeek API vs Eden AI](https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai.md)\n- [DeepSeek API vs SiliconFlow](https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.md)\n- [Eden AI vs Glimpse](https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse.md)\n- [Eden AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.md)\n- [Eden AI vs Gemini Developer API](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api.md)\n- [Eden AI vs GroqCloud](https://www.anchorterminal.com/compare/eden-ai-vs-groq.md)\n- [Eden AI vs Inkling 2 Small](https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.md)\n- [Eden AI vs Jais 3](https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.md)\n- [Eden AI vs Meta Model API](https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.md)\n- [Eden AI vs MiniMax API](https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api.md)\n- [Eden AI vs Mistral AI API](https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api.md)\n- [Eden AI vs Muse Spark Open](https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.md)\n- [Eden AI vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl.md)\n- [Eden AI vs Novita AI](https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.md)\n- [Eden AI vs OpenAI API](https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.md)\n- [Eden AI vs Prism Inference](https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference.md)\n- [Eden AI vs Beam 1.0](https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.md)\n- [Eden AI vs SambaCloud](https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.md)\n- [Eden AI vs Simplismart](https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.md)\n- [Eden AI vs StepFun API](https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.md)\n- [Eden AI vs SWE-2 Flash](https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash.md)\n- [Eden AI vs Together AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.md)\n- [Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.md)\n- [Eden AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.md)\n- [Glimpse vs SiliconFlow](https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow.md)\n- [Fireworks AI Inference vs 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