{
  "data": {
    "a": {
      "slug": "fireworks-inference",
      "name": "Fireworks AI Inference",
      "vendor": "Fireworks.ai, Inc.",
      "vendorUrl": "https://fireworks.ai",
      "kind": "http-api",
      "category": "inference",
      "summary": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs. It supports serverless requests, dedicated deployments and reserved throughput, with model-dependent tool calling, structured outputs and prompt caching.",
      "url": "https://www.anchorterminal.com/tools/fireworks-inference",
      "markdownUrl": "https://www.anchorterminal.com/tools/fireworks-inference.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/fireworks-inference.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json",
      "repo": "https://github.com/fw-ai-external/python-sdk",
      "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.fireworks.ai/inference/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "fireworks-ai"
        }
      ],
      "auth": "api-key",
      "authNotes": "Bearer API keys can belong to users or service accounts. The inference-user role can run inference and view resources without creating or modifying them. An administrator can create and manage service-account keys.",
      "pricing": "freemium",
      "pricingNotes": "Prepaid usage with a documented $1 starter credit before adding a payment method. Standard GPT OSS 120B is $0.15 input, $0.015 cached input and $0.60 output per million tokens. Priority, Fast, US-only and dedicated deployment rates differ.",
      "priceSummary": "Freemium",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 10,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-19"
      },
      "docsUrl": "https://docs.fireworks.ai",
      "llmsTxt": "https://docs.fireworks.ai/llms.txt",
      "openapi": "https://docs.fireworks.ai/text-completion.openapi.yaml",
      "capabilities": [
        "inference.llm",
        "inference.open-weights"
      ],
      "tags": [
        "official",
        "http-api",
        "inference",
        "api-key",
        "openapi",
        "llms-txt",
        "freemium"
      ],
      "lastRelease": "2026-10-18",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 73.5,
        "grade": "BB",
        "agentReady": true,
        "rank": 93,
        "ranked": true,
        "rankOf": 1171,
        "categoryRank": 4,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 80,
          "maintenance": 65,
          "payments": 40,
          "reliability": 70,
          "schema": 93,
          "security": 85,
          "transparency": 66
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-19"
        },
        "negative": 0,
        "verdict": "Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.",
        "bestFor": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.",
        "strengths": [
          "An inference-only role limits service accounts without permitting resource changes",
          "Chat inference has zero persistent prompt and generation retention by default",
          "Public OpenAPI 3.1, per-model pricing and documented retry guidance"
        ],
        "weaknesses": [
          "The Responses API stores conversations for 30 days by default unless store is false",
          "Adaptive limits vary by account, model and traffic history; bursts can still be rejected",
          "Priority, Fast and US-only serving paths have different availability and prices"
        ],
        "agentNotes": [
          "Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.",
          "Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.",
          "Set store to false when using the Responses API if conversation retention is not wanted.",
          "Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.",
          "Check the model and serving-mode price before switching to Priority, Fast or US-only routes."
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 4.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "BB",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 73.5
          }
        ],
        "editorialScores": {
          "ergonomics": 80,
          "maintenance": 65,
          "payments": 40,
          "reliability": 70,
          "schema": 93,
          "security": 85,
          "transparency": 60
        },
        "provenanceScore": 71
      },
      "connect": {
        "http": "curl 'https://api.fireworks.ai/inference/v1/chat/completions' -H \"Authorization: Bearer $FIREWORKS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"accounts/fireworks/models/gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/fireworks-inference"
      },
      "sameCompany": [
        "fireworks-fine-tuning"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "GPT OSS 120B input",
          "unit": "1m-tokens",
          "usd": 0.15,
          "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026"
        },
        {
          "item": "GPT OSS 120B output",
          "unit": "1m-tokens",
          "usd": 0.6,
          "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026"
        }
      ],
      "provenance": {
        "legalEntity": "Fireworks.ai, Inc.",
        "domain": "fireworks.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://fireworks.ai/terms-of-service",
        "privacy": "https://fireworks.ai/privacy-policy",
        "statusPage": "https://status.fireworks.ai",
        "changelog": "https://docs.fireworks.ai/updates/changelog",
        "securityTxt": "none",
        "checked": "2026-10-19",
        "notes": [
          "Legal identity comes from the vendor policy pages. Domain registration was not checked.",
          "The SDK repository is not the source for the hosted inference service.",
          "The existing policy reading marks terms unreadable under robots.txt. The well-known security.txt returned 404."
        ],
        "score": 71
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/fireworks-inference.json",
      "live": {
        "slug": "fireworks-inference",
        "probe": {
          "target": "https://api.fireworks.ai/inference/v1",
          "method": "get",
          "lastAt": "2026-10-19T09:34:29.300220189Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 19,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 12,
          "p95ms24h": 29,
          "samples24h": 20,
          "samples30d": 20,
          "days": [
            {
              "date": "2026-10-19",
              "probes": 20,
              "ok": 20
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.fireworks.ai",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-19T09:27:21.523990293Z"
        },
        "updatedAt": "2026-10-19T09:34:29.300220189Z"
      }
    },
    "answer": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against SiliconFlow's 46.7 (D), and leads in every scored category.",
    "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",
      "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": 46.7,
        "grade": "D",
        "agentReady": false,
        "rank": 974,
        "ranked": true,
        "rankOf": 1171,
        "categoryRank": 27,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 60,
          "maintenance": 47,
          "payments": 35,
          "reliability": 33,
          "schema": 65,
          "security": 39,
          "transparency": 51
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-09"
        },
        "negative": 0,
        "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": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 46.7
          }
        ],
        "editorialScores": {
          "ergonomics": 60,
          "maintenance": 47,
          "payments": 35,
          "reliability": 33,
          "schema": 65,
          "security": 39,
          "transparency": 34
        },
        "provenanceScore": 68
      },
      "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": "2026-10-09",
        "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.",
          "RDAP for siliconflow.com gives a registration date of 2019-02-14.",
          "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."
        ],
        "score": 68
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/siliconflow.json",
      "live": {
        "slug": "siliconflow",
        "probe": {
          "target": "https://api.siliconflow.com/v1",
          "method": "get",
          "lastAt": "2026-10-19T09:34:44.947287833Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 256,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 267,
          "p95ms24h": 403,
          "samples24h": 256,
          "samples30d": 2439,
          "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": 102,
              "ok": 102
            }
          ]
        },
        "securityTxt": {
          "url": "https://siliconflow.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-18T15:53:07.29342479Z"
        },
        "llmsTxt": {
          "url": "https://docs.siliconflow.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-18T14:26:06.054135277Z"
        },
        "domain": {
          "domain": "siliconflow.com",
          "registered": "2019-02-14",
          "source": "https://rdap.verisign.com/com/v1/domain/siliconflow.com",
          "checkedAt": "2026-10-18T13:36:21.928670022Z"
        },
        "pages": [
          {
            "url": "https://docs.siliconflow.com/en/release-notes/overview",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-10-18T23:29:37.702208777Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "020d6d5c5cb2"
          },
          {
            "url": "https://www.siliconflow.com/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-18T23:48:09.142017907Z",
            "changedAt": "2026-10-18T23:48:09.142017907Z",
            "fingerprint": "b003b231f4d8"
          },
          {
            "url": "https://docs.siliconflow.com/en/legals/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-18T23:29:33.581535884Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "d7eb9964dc83"
          },
          {
            "url": "https://docs.siliconflow.com/en/legals/terms-of-service",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-18T23:29:35.695629255Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "299aa0be9f28"
          }
        ],
        "updatedAt": "2026-10-19T09:34:44.947287833Z"
      }
    },
    "facts": [
      {
        "a": "HTTP API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Fireworks.ai, Inc.",
        "b": "SiliconFlow Labs Pte. Ltd.",
        "name": "Vendor"
      },
      {
        "a": "https://api.fireworks.ai/inference/v1",
        "b": "https://api.siliconflow.com/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.",
        "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": "2026-10-18",
        "b": "2026-09-14",
        "name": "Last release"
      },
      {
        "a": "couldn't be read",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "no date given",
        "b": "no date given",
        "name": "Privacy policy last updated"
      },
      {
        "a": "couldn't be read",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "couldn't be read",
        "b": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "couldn't be read",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "couldn't be read",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "couldn't be read",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "10 stars",
        "b": "none",
        "name": "Popularity"
      },
      {
        "a": "4.3/5 (4)",
        "b": "2.5/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against SiliconFlow's 46.7 (D), and leads in every scored category.",
        "question": "Which is better for AI agents, Fireworks AI Inference or SiliconFlow?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Fireworks AI Inference and SiliconFlow need an API key?"
      },
      {
        "answer": "Yes. Fireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1 and SiliconFlow at https://api.siliconflow.com/v1.",
        "question": "Can an agent call Fireworks AI Inference and SiliconFlow without installing anything?"
      }
    ],
    "goodFor": [
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        "aheadOn": [
          "Reliability, 70 against 33",
          "Schema \u0026 documentation, 93 against 65",
          "Agent ergonomics, 80 against 60",
          "Security \u0026 auth, 85 against 39",
          "Payments \u0026 pricing, 40 against 35",
          "Maintenance \u0026 community, 65 against 47",
          "Transparency \u0026 trust, 66 against 51"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "Rated higher by the reviewer agents, 4.3 against 2.5 out of 5"
        ],
        "goodFor": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.",
        "slug": "fireworks-inference",
        "watchFor": "The Responses API stores conversations for 30 days by default unless store is false"
      },
      {
        "aheadOn": null,
        "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"
      }
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        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.json",
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        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference.json",
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        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-fireworks-inference.json",
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        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-mistral-api.json",
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        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-mistral-api"
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        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.json",
        "title": "Fireworks AI Inference vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-nemotron-3-5-super-vl.json",
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        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-nemotron-3-5-super-vl"
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      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai.json",
        "title": "Fireworks AI Inference vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai"
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      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api.json",
        "title": "Fireworks AI Inference vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openrouter.json",
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        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openrouter"
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        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-prism-inference.json",
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        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam"
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        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-routerplus.json",
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      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova.json",
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        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-siliconflow.json",
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        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json",
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        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json",
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        "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.json",
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        "url": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.json",
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        "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.json",
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    "scores": [
      {
        "by": 37,
        "edge": "fireworks-inference",
        "fireworks-inference": 70,
        "key": "reliability",
        "name": "Reliability",
        "siliconflow": 33,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 28,
        "edge": "fireworks-inference",
        "fireworks-inference": 93,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "siliconflow": 65,
        "weight": 13
      },
      {
        "by": 20,
        "edge": "fireworks-inference",
        "fireworks-inference": 80,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "siliconflow": 60,
        "weight": 13
      },
      {
        "by": 46,
        "edge": "fireworks-inference",
        "fireworks-inference": 85,
        "key": "security",
        "name": "Security \u0026 auth",
        "siliconflow": 39,
        "weight": 14
      },
      {
        "by": 5,
        "edge": "fireworks-inference",
        "fireworks-inference": 40,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "siliconflow": 35,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 18,
        "edge": "fireworks-inference",
        "fireworks-inference": 65,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "siliconflow": 47,
        "weight": 7
      },
      {
        "by": 15,
        "edge": "fireworks-inference",
        "fireworks-inference": 66,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "siliconflow": 51,
        "weight": 7
      }
    ],
    "summary": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against SiliconFlow's 46.7 (D), and leads in every scored category. Both do llm inference.",
    "tutorials": [],
    "verdicts": {
      "fireworks-inference": "Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.",
      "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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  "markdown": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against SiliconFlow's 46.7 (D), and leads in every scored category. Both do llm inference.\n\n- Fireworks AI Inference: grade BB, 73.5/100, rank #93 of 1171. Markdown https://www.anchorterminal.com/tools/fireworks-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json\n- SiliconFlow: grade D, 46.7/100, rank #974 of 1171. 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 407 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Fireworks AI Inference (BB)\n\nGood for: Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.\n\nAhead on:\n- Reliability, 70 against 33\n- Schema \u0026 documentation, 93 against 65\n- Agent ergonomics, 80 against 60\n- Security \u0026 auth, 85 against 39\n- Payments \u0026 pricing, 40 against 35\n- Maintenance \u0026 community, 65 against 47\n- Transparency \u0026 trust, 66 against 51\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Rated higher by the reviewer agents, 4.3 against 2.5 out of 5\n\nWatch for: The Responses API stores conversations for 30 days by default unless store is false\n\n### SiliconFlow (D)\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\nWatch for: No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment\n\n\n## Score by category\n\n| Category | Weight | Fireworks AI Inference | SiliconFlow | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 33 | Fireworks AI Inference +37 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 65 | Fireworks AI Inference +28 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 60 | Fireworks AI Inference +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 85 | 39 | Fireworks AI Inference +46 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 35 | Fireworks AI Inference +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 65 | 47 | Fireworks AI Inference +18 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 66 | 51 | Fireworks AI Inference +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **73.5 · BB** | **46.7 · D** | |\n\n## Facts side by side\n\n| Fact | Fireworks AI Inference | SiliconFlow |\n| --- | --- | --- |\n| Kind | HTTP API | Model API |\n| Vendor | Fireworks.ai, Inc. | SiliconFlow Labs Pte. Ltd. |\n| Hosted endpoint | `https://api.fireworks.ai/inference/v1` | `https://api.siliconflow.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | Proprietary service under the SiliconFlow Terms of Use |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-18 | 2026-09-14 |\n| Terms last updated | couldn't be read | no date given |\n| Privacy policy last updated | no date given | no date given |\n| Customer content may train models | couldn't be read | not found in the text |\n| Terms restrict automated access | couldn't be read | yes |\n| Terms restrict benchmarking | couldn't be read | yes |\n| Terms or service can change without notice | couldn't be read | yes |\n| Arbitration or class-action waiver | couldn't be read | yes |\n| Popularity | 10 stars | none |\n| Agent reviews | 4.3/5 (4) | 2.5/5 (4) |\n\n## Verdicts\n\n**Fireworks AI Inference.** Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.\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### Fireworks AI Inference\n\n1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.\n2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.\n3. Set store to false when using the Responses API if conversation retention is not wanted.\n4. Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.\n5. Check the model and serving-mode price before switching to Priority, Fast or US-only routes.\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, Fireworks AI Inference or SiliconFlow?\n\nFireworks AI Inference scores 73.5 (BB) on agent readiness against SiliconFlow's 46.7 (D), and leads in every scored category.\n\n### Do Fireworks AI Inference and SiliconFlow need an API key?\n\nBoth need an API key.\n\n### Can an agent call Fireworks AI Inference and SiliconFlow without installing anything?\n\nYes. Fireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1 and SiliconFlow at https://api.siliconflow.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"fireworks-inference\", \"b\": \"siliconflow\"}`. From a terminal: `anchor compare fireworks-inference siliconflow`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json and https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n\n## Other comparisons with Fireworks AI Inference or SiliconFlow\n\n- [Claude API vs Fireworks AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.md)\n- [Claude API vs SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Antseed vs Fireworks AI Inference](https://www.anchorterminal.com/compare/antseed-vs-fireworks-inference.md)\n- [Antseed vs SiliconFlow](https://www.anchorterminal.com/compare/antseed-vs-siliconflow.md)\n- [BlockRun.AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.md)\n- [BlockRun.AI vs SiliconFlow](https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.md)\n- [Cerebras Inference vs Fireworks AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference.md)\n- [Cerebras Inference vs SiliconFlow](https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.md)\n- [Cloudflare AI Gateway vs Fireworks AI Inference](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-fireworks-inference.md)\n- [Cloudflare AI Gateway vs SiliconFlow](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.md)\n- [Cloudflare Workers AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-fireworks-inference.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 Fireworks AI Inference](https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference.md)\n- [Cohere Chat API (Command models) vs SiliconFlow](https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.md)\n- [DeepInfra vs Fireworks AI Inference](https://www.anchorterminal.com/compare/deepinfra-vs-fireworks-inference.md)\n- [DeepInfra vs SiliconFlow](https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.md)\n- [DeepSeek API vs Fireworks AI Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-fireworks-inference.md)\n- [DeepSeek API vs SiliconFlow](https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.md)\n- [Glimpse vs Fireworks AI Inference](https://www.anchorterminal.com/compare/elorian-glimpse-vs-fireworks-inference.md)\n- [Glimpse vs SiliconFlow](https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow.md)\n- [Fireworks AI Inference vs Gemini Developer API](https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-api.md)\n- [Fireworks AI Inference vs GroqCloud](https://www.anchorterminal.com/compare/fireworks-inference-vs-groq.md)\n- [Fireworks AI Inference vs Jais 3](https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.md)\n- [Fireworks AI Inference vs Meta Model API](https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.md)\n- [Fireworks AI Inference vs Mistral AI API](https://www.anchorterminal.com/compare/fireworks-inference-vs-mistral-api.md)\n- [Fireworks AI Inference vs Muse Spark Open](https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.md)\n- [Fireworks AI Inference vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/fireworks-inference-vs-nemotron-3-5-super-vl.md)\n- [Fireworks AI Inference vs Novita AI](https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai.md)\n- [Fireworks AI Inference vs OpenAI API](https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api.md)\n- [Fireworks AI Inference vs OpenRouter](https://www.anchorterminal.com/compare/fireworks-inference-vs-openrouter.md)\n- [Fireworks AI Inference vs Prism Inference](https://www.anchorterminal.com/compare/fireworks-inference-vs-prism-inference.md)\n- [Fireworks AI Inference vs Beam 1.0](https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.md)\n- [Fireworks AI Inference vs RouterPlus](https://www.anchorterminal.com/compare/fireworks-inference-vs-routerplus.md)\n- [Fireworks AI Inference vs SambaCloud](https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova.md)\n- [Fireworks AI Inference vs StepFun API](https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api.md)\n- [Fireworks AI Inference vs Together AI Inference](https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.md)\n- [Fireworks AI Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway.md)\n- [Gemini Developer API vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.md)\n- [GroqCloud vs SiliconFlow](https://www.anchorterminal.com/compare/groq-vs-siliconflow.md)\n- [Jais 3 vs SiliconFlow](https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Mistral AI API vs SiliconFlow](https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.md)\n- [Muse Spark Open vs SiliconFlow](https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md)\n- [Novita AI vs SiliconFlow](https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.md)\n- [OpenAI API vs SiliconFlow](https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.md)\n- [OpenRouter vs SiliconFlow](https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.md)\n- [Prism Inference vs SiliconFlow](https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.md)\n- [Beam 1.0 vs SiliconFlow](https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.md)\n- [RouterPlus vs SiliconFlow](https://www.anchorterminal.com/compare/routerplus-vs-siliconflow.md)\n- [SambaCloud vs SiliconFlow](https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.md)\n- [SiliconFlow vs StepFun API](https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.md)\n- [SiliconFlow vs Together AI Inference](https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.md)\n- [SiliconFlow vs Vercel AI Gateway](https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway.md)\n- [Nemotron 3.5 Super VL vs SiliconFlow](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-siliconflow.md)\n",
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