{
  "data": {
    "a": {
      "slug": "cohere-chat",
      "name": "Cohere Chat API (Command models)",
      "vendor": "Cohere",
      "vendorUrl": "https://cohere.com",
      "kind": "model",
      "category": "inference",
      "summary": "Cohere's Chat API generates text with the Command family of models over REST (v2 chat), with tool use, structured outputs, citations and streaming. SDKs cover Python, TypeScript, Java and Go.",
      "url": "https://www.anchorterminal.com/tools/cohere-chat",
      "markdownUrl": "https://www.anchorterminal.com/tools/cohere-chat.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cohere-chat.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cohere-chat.json",
      "dns": "cohere-chat.grade.anchorterminal.com",
      "repo": "https://github.com/cohere-ai/cohere-python",
      "license": "Proprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MIT",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.cohere.com/v2/chat",
      "packages": [
        {
          "registry": "pypi",
          "name": "cohere",
          "main": true
        },
        {
          "registry": "npm",
          "name": "cohere-ai",
          "main": true
        },
        {
          "registry": "go",
          "name": "github.com/cohere-ai/cohere-go/v2"
        }
      ],
      "auth": "api-key",
      "authNotes": "Bearer API key from the dashboard, self-serve. A trial key is created at sign-up. A production key needs a team Owner to complete the Go to Production form and accept the SaaS agreement. Team roles are Owner and User. No key scopes or expiry were found in the docs.",
      "pricing": "freemium",
      "pricingNotes": "Trial keys are free with no card, limited to 20 chat requests a minute and 1,000 calls a month, and not for commercial use. Production keys bill per input and output token, monthly or at $250 outstanding. The pricing page lists Command R at $0.15 and $0.60 and Command R7B at $0.0375 and $0.15 per million input and output tokens, Command R+ 08-2024 at $2.50 and $10.00 among legacy prices, and Command A+ as free. No price is published for Command A, Reasoning, Vision or Translate. Production keys stay at trial limits on Command A+, Reasoning, Translate and Vision (checked 2026-11-02).",
      "priceSummary": "from $0.0375 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs, 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.cohere.com/docs/chat-api",
      "rateLimitsUrl": "https://docs.cohere.com/docs/rate-limits",
      "llmsTxt": "https://docs.cohere.com/llms.txt",
      "openapi": "https://raw.githubusercontent.com/cohere-ai/cohere-developer-experience/main/cohere-openapi.yaml",
      "capabilities": [
        "inference.llm",
        "inference.open-weights"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "free-tier",
        "no-card",
        "openapi",
        "llms-txt",
        "openai-compatible",
        "python",
        "typescript",
        "java",
        "go",
        "status-page",
        "soc2",
        "bug-bounty"
      ],
      "lastRelease": "2026-09-09",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 65.6,
        "grade": "B",
        "agentReady": false,
        "rank": 409,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 17,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 72,
          "maintenance": 72,
          "payments": 35,
          "reliability": 67,
          "schema": 84,
          "security": 55,
          "transparency": 75
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-02"
        },
        "negative": 0,
        "verdict": "A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.",
        "bestFor": "Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.",
        "strengths": [
          "Public OpenAPI 3.1 file in the docs repository, last changed 29 September 2026, and a Markdown twin of every docs page",
          "A trial key is created at sign-up with no card, limited to 20 chat requests a minute and 1,000 calls a month",
          "Official SDKs for Python, TypeScript and Go, each tagged on 21 October 2026, and Java 1.12.0",
          "JSON Schema structured outputs, `strict_tools` (beta), citations, reasoning budgets and safety modes on the v2 chat request",
          "The trust centre lists SOC 2 Type II, ISO 27001, ISO 42001 and a bug bounty, with nine sub-processors, all in the US"
        ],
        "weaknesses": [
          "Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault",
          "The pricing page lists per-token prices for Command R, R7B and R+ only. Command A, Reasoning, Vision and Translate have no published price",
          "The SaaS agreement of 8 April 2025 grants Cohere an irrevocable right to use API data to improve its services and to share it with third parties",
          "No Retry-After header, backoff guidance or idempotency key was found in the reviewed documentation",
          "The SaaS agreement forbids use of the services for benchmarking or competitive analysis. Recorded as a fact, and it matters before any probe is run"
        ],
        "agentNotes": [
          "Call `POST https://api.cohere.com/v2/chat` with `Authorization: bearer \u003ckey\u003e`. `model` and `messages` are the only required fields",
          "Use `command-a-03-2025`, `command-r-08-2024`, `command-r-plus-08-2024` or `command-r7b-12-2024` for production traffic. Newer variants stay at trial limits on a production key, and only the R models have published prices",
          "Keep a trial key under 20 chat requests a minute and 1,000 calls a month, and do not use it for commercial work",
          "Set `response_format` with a `json_schema` for structured output, and tell the model to produce JSON when using `json_object` without a schema",
          "Ask the account Owner to turn off training under Data Controls in the dashboard before sending confidential prompts"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 65.6
          }
        ],
        "editorialScores": {
          "ergonomics": 72,
          "maintenance": 72,
          "payments": 35,
          "reliability": 67,
          "schema": 84,
          "security": 55,
          "transparency": 66
        },
        "provenanceScore": 84,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-02",
            "maintenance": "2026-11-02",
            "payments": "2026-11-02",
            "reliability": "2026-11-02",
            "schema": "2026-11-02",
            "security": "2026-11-02",
            "transparency": "2026-11-02"
          },
          "last": "2026-11-02",
          "lastMoved": "2026-11-02",
          "oldest": "2026-11-02",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install cohere   # or: npm i cohere-ai",
        "http": "curl --request POST \\\n  --url https://api.cohere.ai/v2/chat \\\n  --header 'accept: application/json' \\\n  --header 'content-type: application/json' \\\n  --header \"Authorization: bearer $CO_API_KEY\" \\\n  --data '{\"model\":\"command-a-plus-05-2026\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/cohere-chat"
      },
      "sameCompany": [
        "cohere-embed",
        "cohere-transcribe-03-2026",
        "cohere-north"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "Command R input",
          "unit": "1m-tokens",
          "usd": 0.15
        },
        {
          "item": "Command R output",
          "unit": "1m-tokens",
          "usd": 0.6
        },
        {
          "item": "Command R7B input",
          "unit": "1m-tokens",
          "usd": 0.0375
        },
        {
          "item": "Command R7B output",
          "unit": "1m-tokens",
          "usd": 0.15
        },
        {
          "item": "Command R+ 08-2024 input",
          "unit": "1m-tokens",
          "usd": 2.5,
          "note": "Listed among legacy prices"
        },
        {
          "item": "Command R+ 08-2024 output",
          "unit": "1m-tokens",
          "usd": 10,
          "note": "Listed among legacy prices"
        }
      ],
      "provenance": {
        "legalEntity": "Cohere Inc.",
        "domain": "cohere.com",
        "domainRegistered": "2000-03-07",
        "endpointOnVendorDomain": true,
        "terms": "https://cohere.com/saas-agreement",
        "privacy": "https://cohere.com/privacy",
        "statusPage": "https://status.cohere.com",
        "changelog": "https://docs.cohere.com/v2/changelog",
        "securityTxt": "none",
        "checked": "2026-10-09",
        "notes": [
          "The Commercial SaaS Agreement (last updated 8 April 2025) names Cohere Inc., 171 John Street, Suite 200, Toronto, Ontario, and is governed by Ontario law.",
          "The privacy policy (last updated 1 May 2026) says it does not apply to customer inputs and outputs under an enterprise agreement, which the agreement and a DPA govern. The DPA is sent on request.",
          "The OpenAPI file names https://api.cohere.com as the server and the chat guide's examples call https://api.cohere.ai. Both are Cohere's.",
          "cohere.com/.well-known/security.txt answers 404. The trust centre holds a responsible disclosure policy for the bug bounty.",
          "status.cohere.ai redirects to status.cohere.com, whose robots.txt answers 404, so the host publishes no rules.",
          "RDAP for cohere.com gives a registration date of 2000-03-07."
        ],
        "score": 84
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/cohere-chat.json",
      "live": {
        "slug": "cohere-chat",
        "probe": {
          "target": "https://api.cohere.com/v2/chat",
          "method": "get",
          "lastAt": "2026-11-07T19:22:00.421763053Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 202,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 147,
          "p95ms24h": 240,
          "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": 253
            },
            {
              "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": 251,
              "ok": 251
            },
            {
              "date": "2026-10-29",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-30",
              "probes": 248,
              "ok": 248
            },
            {
              "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
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.cohere.com",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-11-07T19:21:31.446185992Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "cohere-ai/cohere-python",
            "version": "7.3.2",
            "released": "2026-11-04",
            "seenAt": "2026-11-06T23:16:28.900178589Z"
          },
          {
            "registry": "npm",
            "name": "cohere-ai",
            "version": "8.3.1",
            "seenAt": "2026-11-06T23:16:28.548336782Z"
          },
          {
            "registry": "pypi",
            "name": "cohere",
            "version": "7.3.1",
            "released": "2026-11-04",
            "seenAt": "2026-11-06T23:16:28.43430084Z"
          }
        ],
        "githubStars": 407,
        "npmWeekly": 665965,
        "pypiWeekly": 2576815,
        "securityTxt": {
          "url": "https://cohere.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-07T16:01:21.413669602Z"
        },
        "llmsTxt": {
          "url": "https://docs.cohere.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:06.118223513Z"
        },
        "domain": {
          "domain": "cohere.com",
          "registered": "2000-03-07",
          "source": "https://rdap.verisign.com/com/v1/domain/cohere.com",
          "checkedAt": "2026-11-01T14:17:56.515021491Z"
        },
        "pages": [
          {
            "url": "https://docs.cohere.com/v2/changelog",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-07T14:05:42.882438737Z",
            "changedAt": "2026-11-05T12:29:46.428343553Z",
            "fingerprint": "de6e890a268c"
          },
          {
            "url": "https://docs.cohere.com/docs/deprecations",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-11-07T14:05:40.811028032Z",
            "changedAt": "2026-11-05T12:29:44.384806051Z",
            "fingerprint": "a4d483f2b397"
          },
          {
            "url": "https://cohere.com/privacy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-07T14:01:41.226639318Z",
            "changedAt": "2026-11-06T13:24:23.148883162Z",
            "fingerprint": "1028bd69de2b"
          },
          {
            "url": "https://cohere.com/saas-agreement",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-07T14:01:43.258823927Z",
            "changedAt": "2026-11-06T13:24:25.375763846Z",
            "fingerprint": "0bbd8836589f"
          }
        ],
        "models": {
          "command-r-08-2024": {
            "openrouterId": "cohere/command-r-08-2024",
            "tools": true,
            "structuredOutputs": true,
            "jsonMode": true,
            "reasoning": false,
            "input": [
              "text"
            ],
            "promptCaching": false,
            "contextTokens": 128000,
            "maxOutput": 4000,
            "checkedAt": "2026-11-06T23:49:25.225778715Z"
          },
          "command-r-plus-08-2024": {
            "openrouterId": "cohere/command-r-plus-08-2024",
            "tools": true,
            "structuredOutputs": true,
            "jsonMode": true,
            "reasoning": false,
            "input": [
              "text"
            ],
            "promptCaching": false,
            "contextTokens": 128000,
            "maxOutput": 4000,
            "checkedAt": "2026-11-06T23:49:25.225778715Z"
          },
          "command-r7b-12-2024": {
            "openrouterId": "cohere/command-r7b-12-2024",
            "tools": false,
            "structuredOutputs": true,
            "jsonMode": true,
            "reasoning": false,
            "input": [
              "text"
            ],
            "promptCaching": false,
            "contextTokens": 128000,
            "maxOutput": 4000,
            "checkedAt": "2026-11-06T23:49:25.225778715Z"
          }
        },
        "github": {
          "repo": "cohere-ai/cohere-python",
          "checkedAt": "2026-11-02T08:40:26.40131968Z",
          "stars": 407,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-10-27T15:54:03Z",
          "openIssues": 0,
          "openPRs": 19,
          "issuesOpened90d": 10,
          "issuesClosed90d": 10,
          "prsMerged90d": 7,
          "ci": {
            "branch": "main",
            "runs": 43,
            "success": 34,
            "failure": 9,
            "other": 0,
            "latest": "failure",
            "latestAt": "2026-10-27T16:05:54Z"
          },
          "replies": {
            "sampled": 25,
            "unanswered": 0,
            "medianDays": 9.2
          }
        },
        "updatedAt": "2026-11-07T19:22:00.421763053Z"
      }
    },
    "answer": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth and maintenance \u0026 community.",
    "b": {
      "slug": "hugging-face-inference-providers",
      "name": "Hugging Face Inference Providers",
      "vendor": "Hugging Face, Inc.",
      "vendorUrl": "https://huggingface.co",
      "kind": "router",
      "category": "inference",
      "summary": "Hugging Face's serverless router that sends model calls to partner inference providers such as Groq, Cerebras, Together and Fireworks through one Hugging Face token, with an OpenAI-compatible API at router.huggingface.co/v1 and Python and JavaScript clients.",
      "url": "https://www.anchorterminal.com/tools/hugging-face-inference-providers",
      "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json",
      "dns": "hugging-face-inference-providers.grade.anchorterminal.com",
      "repo": "https://github.com/huggingface/huggingface_hub",
      "license": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://router.huggingface.co/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "huggingface_hub"
        },
        {
          "registry": "npm",
          "name": "@huggingface/inference"
        }
      ],
      "auth": "api-key",
      "authNotes": "Hugging Face user access token sent as `Authorization: Bearer $HF_TOKEN`. The docs recommend a fine-grained token with only the `Make calls to Inference Providers` permission. Tokens are made in account settings in a browser, can be rotated and revoked, and a leaked token can be revoked by anyone through `POST /api/credentials/revoke`. A provider's own key can be stored in settings instead, and Hugging Face swaps it in when routing.",
      "pricing": "usage",
      "pricingNotes": "Pay as you go at each provider's own per-token rates with no Hugging Face markup, drawn from prepaid credits on the Hugging Face account. Free users get no included credits since 7 October 2026 and must buy credits. PRO users and Team or Enterprise seats get $2.00 a month of compute credits. Requests with a custom provider key are billed by the provider (https://huggingface.co/docs/inference-providers/pricing, checked 2026-11-06).",
      "priceSummary": "$2 / mo",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the Inference Providers docs, llms.txt or the router's model list. Calls draw on prepaid Hugging Face credits bought in the account's billing settings (checked 2026-11-06).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": 483470,
        "pypiWeekly": 71518708,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://huggingface.co/docs/inference-providers/index",
      "llmsTxt": "https://huggingface.co/docs/inference-providers/llms.txt",
      "capabilities": [
        "inference.router",
        "inference.open-weights",
        "inference.llm"
      ],
      "tags": [
        "hosted",
        "router",
        "usage",
        "prepaid",
        "openai-compatible",
        "llms-txt",
        "python",
        "javascript",
        "status-page",
        "soc2"
      ],
      "lastRelease": "2026-10-29",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 54,
        "grade": "C",
        "agentReady": false,
        "rank": 926,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 28,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 58,
          "maintenance": 80,
          "payments": 20,
          "reliability": 25,
          "schema": 62,
          "security": 79,
          "transparency": 71
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.",
        "bestFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.",
        "strengths": [
          "router.huggingface.co/v1/models lists every routed model with each provider's price, context, tool support, latency and throughput, without a token",
          "Provider choice by suffix (`:fastest`, `:cheapest`, `:preferred` or a provider name) on an OpenAI-compatible endpoint",
          "Fine-grained tokens can be limited to the `Make calls to Inference Providers` permission and revoked at once",
          "No markup on provider rates, and request bodies and responses are not stored when routed",
          "Official clients in Python (`huggingface_hub` 2.4.0, 29 October 2026) and JavaScript (`@huggingface/inference` 4.13.32)"
        ],
        "weaknesses": [
          "No rate limits, 429 behaviour or error responses documented for the router",
          "status.huggingface.co has no component for Inference Providers or the router",
          "Free users have had no included credits since 7 October 2026, and buying credits needs a person in the account settings",
          "No OpenAPI document for the router, no batch API, and the Responses API is beta",
          "Data handling past the router depends on each provider's own policy"
        ],
        "agentNotes": [
          "Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider",
          "Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider",
          "Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation",
          "Back off on 429 without assuming a Retry-After header, since none is documented for the router"
        ],
        "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": 54
          }
        ],
        "editorialScores": {
          "ergonomics": 58,
          "maintenance": 80,
          "payments": 20,
          "reliability": 25,
          "schema": 62,
          "security": 79,
          "transparency": 58
        },
        "provenanceScore": 84,
        "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": {
        "install": "pip install huggingface_hub   # or: pip install openai, with base_url https://router.huggingface.co/v1",
        "http": "curl https://router.huggingface.co/v1/chat/completions \\\n  -H \"Authorization: Bearer $HF_TOKEN\" -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"openai/gpt-oss-120b:fastest\",\"messages\":[{\"role\":\"user\",\"content\":\"How many Gs in huggingface?\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.router",
        "tool": "https://letme.dev/hugging-face-inference-providers"
      },
      "sameCompany": [
        "hugging-face-inference-endpoints",
        "smolagents",
        "carbon-x",
        "smollm3-3b"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "openai/gpt-oss-120b input, cheapest provider listed (DeepInfra)",
          "unit": "1m-tokens",
          "usd": 0.037,
          "note": "Output $0.17. Groq lists $0.15/$0.75 and Cerebras $0.35/$0.75, per the router's model list of 6 November 2026"
        },
        {
          "item": "PRO monthly compute credits",
          "unit": "month",
          "usd": 2,
          "note": "Also $2.00 per seat for Team and Enterprise organisations"
        }
      ],
      "provenance": {
        "legalEntity": "Hugging Face, Inc.",
        "domain": "huggingface.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://huggingface.co/terms-of-service",
        "privacy": "https://huggingface.co/privacy",
        "statusPage": "https://status.huggingface.co",
        "changelog": "https://huggingface.co/changelog",
        "securityTxt": "valid",
        "checked": "2026-11-06",
        "notes": [
          "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc. and define Inference Providers as a hosted service for running inference through an API on Hub models.",
          "huggingface.co/robots.txt and router.huggingface.co/robots.txt allow all. status.huggingface.co serves an empty robots.txt.",
          "status.huggingface.co is a Better Stack page with components for the Hub, git hosting, Inference Endpoints, Spaces, the CDNs and Jobs, and none for Inference Providers or the router.",
          "huggingface.co/changelog covers the whole Hub and had no Inference Providers entry on its first page on 6 November 2026. Dated changes to the docs are in the hub-docs repository's history.",
          "security.txt, privacy policy and subprocessor list as recorded on the Inference Endpoints listing (checked 8 October and 2 November 2026); not re-read for this listing."
        ],
        "score": 84
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.json",
      "live": {
        "slug": "hugging-face-inference-providers",
        "probe": {
          "target": "https://router.huggingface.co/v1",
          "method": "get",
          "lastAt": "2026-11-07T19:22:12.474650545Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 145,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 109,
          "p95ms24h": 196,
          "samples24h": 210,
          "samples30d": 210,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-11-07T04:47:55.542550557Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "huggingface/huggingface_hub",
            "version": "v2.4.0",
            "released": "2026-10-29",
            "seenAt": "2026-11-06T23:33:27.894225298Z"
          },
          {
            "registry": "npm",
            "name": "@huggingface/inference",
            "version": "4.13.32",
            "seenAt": "2026-11-06T23:33:27.102558197Z"
          },
          {
            "registry": "pypi",
            "name": "huggingface_hub",
            "version": "2.4.0",
            "released": "2026-10-29",
            "seenAt": "2026-11-06T23:33:26.910773744Z"
          }
        ],
        "githubStars": 4034,
        "npmWeekly": 483470,
        "pypiWeekly": 71518708,
        "securityTxt": {
          "url": "https://huggingface.co/.well-known/security.txt",
          "state": "valid",
          "expires": "2030-07-01T08:42:00.000Z",
          "checkedAt": "2026-11-07T16:00:00.493446773Z"
        },
        "llmsTxt": {
          "url": "https://huggingface.co/docs/inference-providers/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:44.910268229Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/docs/inference-providers/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-11-07T14:11:37.221950067Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "2cbe821ca9d2"
          }
        ],
        "updatedAt": "2026-11-07T19:22:12.474650545Z"
      }
    },
    "edges": [
      {
        "by": 42,
        "category": "reliability",
        "leads": "cohere-chat",
        "name": "Reliability",
        "reasons": {
          "a": "Hosted lines. status.cohere.com (incident.io) lists each Command model and the endpoints as components (20). Its feed, read on 2 November 2026, shows two incidents in the 90 days from 4 August. 'Multiple Endpoint Disruptions' on 1 September 2026, from 15:41 to 19:47 UTC, degraded the embeddings endpoint, embed-v4.0, two rerank models and `command-a-reasoning-08-2025` during a Google Cloud outage, rated minor and partial, and docs loading failed on 5 August. Nothing has been posted since 1 September, so minor incidents only (20). Chat limits are published per model, 20 requests a minute and 1,000 calls a month on a trial key and 500 a minute on a production key for Command A, R, R+ and R7B, while the four newest variants say contact sales (12 of 15). The errors page documents 429 with example messages that say to wait and try again later and links to the rate limits, with no Retry-After header, backoff timing or idempotency key, the reading cohere-embed takes of the same page (8 of 15). cohere.com/slo is titled Service Level Objective and its text is script-drawn, so it was unread and scores as absent (0). The v2 chat endpoint is the default docs version, but the sample response on the chat guide still carries `is_experimental` and the newest models are not open to production keys (7 of 10).",
          "b": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score."
        },
        "scores": {
          "a": 67,
          "b": 25
        }
      },
      {
        "by": 24,
        "category": "security",
        "leads": "hugging-face-inference-providers",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Model reading. Bearer keys of two kinds, trial and production. Team roles are Owner and User, only Owners delete production keys, and a production key is shown in full once. No scopes, expiry or per-model restriction was found (18 of 30). Paying customers can switch training off under Data Controls, which implies it is on until they do, trial keys fall under the website terms, and the SaaS agreement grants an irrevocable right to use API data to improve the services and share it with third parties (8 of 20). Logged prompts and generations are deleted after 30 days unless flagged, and zero data retention needs approval (12 of 15). The dashboard shows usage history, and no customer audit log was found (2 of 15). The trust centre lists SOC 2 Type II, ISO 27001, ISO 42001, UK Cyber Essentials, penetration tests on request and a responsible disclosure policy with a bug bounty, per the 9 October check. cohere.com/.well-known/security.txt still answers 404 on 2 November and no public advisories were found, so the line takes 15, as cohere-embed and cohere-north read the same programme (15 of 20).",
          "b": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20)."
        },
        "scores": {
          "a": 55,
          "b": 79
        }
      },
      {
        "by": 22,
        "category": "schema",
        "leads": "cohere-chat",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "Model reading. Public OpenAPI 3.1 file `cohere-openapi.yaml` in cohere-ai/cohere-developer-experience, 43 operations, last changed 29 September 2026 (25). docs.cohere.com/llms.txt and a Markdown twin of every page by adding `.md`, though the llms.txt files list no pages (8 of 10). The v2 chat operation describes each of its 21 request fields with defaults and limits, and says less about when to prefer one option (16 of 20). Enums on `tool_choice`, `safety_mode` and `thinking.type`, numeric bounds on `temperature`, `k`, `p` and `priority`, with penalties bounded only in prose (12 of 15). Eight request examples on the operation and an errors page with sample messages for each status code, with error bodies carrying a message and no machine code (12 of 15). v1 and v2 live side by side in the path and the changelog is dated, but the OpenAPI file is version 1.0 throughout and its changes are committed as 'Add spec changes' with no per-change note (11 of 15).",
          "b": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15)."
        },
        "scores": {
          "a": 84,
          "b": 62
        }
      },
      {
        "by": 15,
        "category": "payments",
        "leads": "cohere-chat",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "No x402, MPP or L402 in the docs, the OpenAPI file or the pricing page (0). The docs say Command models are billed per input and output token. The pricing page, read on 2 November 2026, now carries per-unit prices in its own page data, Command R at $0.15 input and $0.60 output and Command R7B at $0.0375 and $0.15 per million tokens, with Command R+ 08-2024 at $2.50 and $10.00 among legacy prices and Command A+ shown as free. No price is published for Command A, Reasoning, Vision or Translate, so the line takes 15 rather than the full 20 (15 of 20). A trial key is created at sign-up and is free with no card (20). Sign-up is in a browser, and a production key needs an Owner to complete a Go to Production form (0).",
          "b": "No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0)."
        },
        "scores": {
          "a": 35,
          "b": 20
        }
      },
      {
        "by": 14,
        "category": "ergonomics",
        "leads": "cohere-chat",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Model reading. Function calling with `tool_choice` REQUIRED or NONE and `strict_tools`, which the reference marks beta (17 of 20). `response_format` takes `json_object` or a JSON Schema, with limits documented and no support in RAG mode (13 of 15). The usage object reports `cached_tokens`, and no guide or price for prompt caching was found (5 of 15). Context is 256,000 tokens on Command A and Command A Reasoning and 128,000 on Command A+ (10 of 15). `/v2/batches` runs a batch from an uploaded dataset, with no price or discount found (6 of 10). Official SDKs for Python, TypeScript, Java and Go (10). Error messages are specific and readable, with no stable error codes (11 of 15).",
          "b": "Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15)."
        },
        "scores": {
          "a": 72,
          "b": 58
        }
      },
      {
        "by": 8,
        "category": "maintenance",
        "leads": "hugging-face-inference-providers",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "Model reading. The last dated release on the Chat endpoint is still North Small Translate on 9 September 2026, 54 days before this check. The last Command model is Command A+ on 20 May 2026. Rerank 5 (21 October) and Embed 5 (30 September) aren't chat changes, so we score the 90-day band (20 of 30). The deprecations page defines Active, Legacy, Deprecated and Shutdown and promises email notice, with no minimum notice period (6 of 12). No chat model was retired or announced for retirement in the last 90 days. The newest entry on the page is still two Aya models retired on 4 April 2026 (8 of 8). Dated changelog with four entries since 4 August (27 August, 9 September, 30 September, 21 October), one of them for a chat model (12 of 15). SDK issue replies not sampled (5 of 10). Python SDK 7.2.0 and 7.3.0, TypeScript 8.2.0 (19 October) and 8.3.0, and Go v2.20.0 tagged on 21 October 2026, Java at 1.12.0 (15). The Python SDK is generated from the OpenAPI file and has a CI workflow, whose runs we did not read (6 of 10).",
          "b": "Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10)."
        },
        "scores": {
          "a": 72,
          "b": 80
        }
      }
    ],
    "facts": [
      {
        "a": "Model API",
        "b": "Model router",
        "name": "Kind"
      },
      {
        "a": "Cohere",
        "b": "Hugging Face, Inc.",
        "name": "Vendor"
      },
      {
        "a": "https://api.cohere.com/v2/chat",
        "b": "https://router.huggingface.co/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 service under Cohere's Commercial SaaS Agreement. The SDKs are MIT",
        "b": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-09",
        "b": "2026-10-29",
        "name": "Last release"
      },
      {
        "a": "2025-04-08",
        "b": "2022-09-15",
        "name": "Terms last updated"
      },
      {
        "a": "2026-05-01",
        "b": "2023-03-28",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "483k npm/wk, 71.5M PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth and maintenance \u0026 community.",
        "question": "Which is better for AI agents, Cohere Chat API (Command models) or Hugging Face Inference Providers?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Cohere Chat API (Command models) and Hugging Face Inference Providers need an API key?"
      },
      {
        "answer": "Yes. Cohere Chat API (Command models) has a hosted endpoint at https://api.cohere.com/v2/chat and Hugging Face Inference Providers at https://router.huggingface.co/v1.",
        "question": "Can an agent call Cohere Chat API (Command models) and Hugging Face Inference Providers without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 67 against 25",
          "Schema \u0026 documentation, 84 against 62",
          "Agent ergonomics, 72 against 58",
          "Payments \u0026 pricing, 35 against 20"
        ],
        "also": [
          "Free to start without a card"
        ],
        "goodFor": "Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.",
        "slug": "cohere-chat",
        "watchFor": "Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault"
      },
      {
        "aheadOn": [
          "Security \u0026 auth, 79 against 55",
          "Maintenance \u0026 community, 80 against 72"
        ],
        "also": null,
        "goodFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.",
        "slug": "hugging-face-inference-providers",
        "watchFor": "No rate limits, 429 behaviour or error responses documented for the router"
      }
    ],
    "history": {
      "cohere-chat": [
        {
          "causes": [
            "evidence",
            "correction"
          ],
          "date": "2026-11-02",
          "delta": 0.9,
          "from": 64.7,
          "fromGrade": "B",
          "to": 65.6,
          "toGrade": "B"
        },
        {
          "causes": [
            "method"
          ],
          "date": "2026-10-28",
          "delta": 0,
          "from": 64.7,
          "fromGrade": "B",
          "to": 64.7,
          "toGrade": "B"
        }
      ],
      "hugging-face-inference-providers": null
    },
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat.json",
        "title": "Amazon Bedrock vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.json",
        "title": "Amazon Bedrock vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.json",
        "title": "Claude API vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.json",
        "title": "Claude API vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-cohere-chat.json",
        "title": "Antseed vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.json",
        "title": "Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.json",
        "title": "Azure OpenAI in Foundry Models vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-cohere-chat.json",
        "title": "BlockRun.AI vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.json",
        "title": "BlockRun.AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cohere-chat.json",
        "title": "Cerebras Inference vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.json",
        "title": "Cerebras Inference vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-cohere-chat.json",
        "title": "Cloudflare AI Gateway vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hugging-face-inference-providers.json",
        "title": "Cloudflare AI Gateway vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-cohere-chat.json",
        "title": "Cloudflare Workers AI vs Cohere Chat API (Command models)",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-cohere-chat"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hugging-face-inference-providers.json",
        "title": "Cloudflare Workers AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepinfra.json",
        "title": "Cohere Chat API (Command models) vs DeepInfra",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepinfra"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api.json",
        "title": "Cohere Chat API (Command models) vs DeepSeek API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api"
      },
      {
        "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-elorian-glimpse.json",
        "title": "Cohere Chat API (Command models) vs Glimpse",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-elorian-glimpse"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference.json",
        "title": "Cohere Chat API (Command models) vs Fireworks AI Inference",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-api.json",
        "title": "Cohere Chat API (Command models) vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq.json",
        "title": "Cohere Chat API (Command models) vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-inkling-2-small.json",
        "title": "Cohere Chat API (Command models) vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.json",
        "title": "Cohere Chat API (Command models) vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.json",
        "title": "Cohere Chat API (Command models) vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-minimax-api.json",
        "title": "Cohere Chat API (Command models) vs MiniMax API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-minimax-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-api.json",
        "title": "Cohere Chat API (Command models) vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.json",
        "title": "Cohere Chat API (Command models) vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-nemotron-3-5-super-vl.json",
        "title": "Cohere Chat API (Command models) vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-nemotron-3-5-super-vl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-novita-ai.json",
        "title": "Cohere Chat API (Command models) vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api.json",
        "title": "Cohere Chat API (Command models) vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-openrouter.json",
        "title": "Cohere Chat API (Command models) vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-prism-inference.json",
        "title": "Cohere Chat API (Command models) vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-ramp-router.json",
        "title": "Cohere Chat API (Command models) vs Router.com (Ramp Router)",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-ramp-router"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.json",
        "title": "Cohere Chat API (Command models) vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-routerplus.json",
        "title": "Cohere Chat API (Command models) vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.json",
        "title": "Cohere Chat API (Command models) vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova"
      },
      {
        "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/cohere-chat-vs-simplismart.json",
        "title": "Cohere Chat API (Command models) vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api.json",
        "title": "Cohere Chat API (Command models) vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-swe-2-flash.json",
        "title": "Cohere Chat API (Command models) vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-tencent-tokenhub.json",
        "title": "Cohere Chat API (Command models) vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference.json",
        "title": "Cohere Chat API (Command models) vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway.json",
        "title": "Cohere Chat API (Command models) vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vercel-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai.json",
        "title": "Cohere Chat API (Command models) vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api.json",
        "title": "Cohere Chat API (Command models) vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-hugging-face-inference-providers.json",
        "title": "DeepInfra vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.json",
        "title": "DeepSeek API vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hugging-face-inference-providers.json",
        "title": "Glimpse vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers.json",
        "title": "Fireworks AI Inference vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.json",
        "title": "Gemini Developer API vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.json",
        "title": "GroqCloud vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small.json",
        "title": "Hugging Face Inference Providers vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-jais-3.json",
        "title": "Hugging Face Inference Providers vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-jais-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.json",
        "title": "Hugging Face Inference Providers vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.json",
        "title": "Hugging Face Inference Providers vs MiniMax API",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-mistral-api.json",
        "title": "Hugging Face Inference Providers vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-spark-open.json",
        "title": "Hugging Face Inference Providers vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai.json",
        "title": "Hugging Face Inference Providers vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api.json",
        "title": "Hugging Face Inference Providers vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.json",
        "title": "Hugging Face Inference Providers vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.json",
        "title": "Hugging Face Inference Providers vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova"
      },
      {
        "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/hugging-face-inference-providers-vs-simplismart.json",
        "title": "Hugging Face Inference Providers vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.json",
        "title": "Hugging Face Inference Providers vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash.json",
        "title": "Hugging Face Inference Providers vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.json",
        "title": "Hugging Face Inference Providers vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.json",
        "title": "Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.json",
        "title": "Hugging Face Inference Providers vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.json",
        "title": "Antseed vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers"
      },
      {
        "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/hugging-face-inference-providers-vs-litellm.json",
        "title": "Hugging Face Inference Providers vs LiteLLM",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter.json",
        "title": "Hugging Face Inference Providers vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.json",
        "title": "Hugging Face Inference Providers vs Router.com (Ramp Router)",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json",
        "title": "Hugging Face Inference Providers vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json",
        "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json",
        "title": "Hugging Face Inference Providers vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json",
        "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json",
        "title": "Hugging Face Inference Providers vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference"
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        "name": "Reliability",
        "weight": 16
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      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
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      {
        "by": 22,
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        "weight": 13
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        "weight": 13
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        "by": 24,
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        "weight": 14
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        "weight": 10
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        "edge": "hugging-face-inference-providers",
        "hugging-face-inference-providers": 80,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 4,
        "cohere-chat": 75,
        "edge": "cohere-chat",
        "hugging-face-inference-providers": 71,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth and maintenance \u0026 community. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "cohere-chat": "A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.",
      "hugging-face-inference-providers": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers",
    "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.min.md"
  },
  "markdown": "Cohere Chat API (Command models) scores 65.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth and maintenance \u0026 community. Both do llm inference.\n\n- Cohere Chat API (Command models): grade B, 65.6/100, rank #409 of 1510. Markdown https://www.anchorterminal.com/tools/cohere-chat.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-chat.json\n- Hugging Face Inference Providers: grade C, 54/100, rank #926 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-providers.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.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### Cohere Chat API (Command models) (B)\n\nGood for: Teams that want Command models for RAG with citations, tool use and multilingual work, and that may later move to a private deployment or Model Vault.\n\nAhead on:\n- Reliability, 67 against 25\n- Schema \u0026 documentation, 84 against 62\n- Agent ergonomics, 72 against 58\n- Payments \u0026 pricing, 35 against 20\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Production keys work like trial keys on Command A+, Reasoning, Translate and Vision. The docs send production use of those models to sales or to Model Vault\n\n### Hugging Face Inference Providers (C)\n\nGood for: Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.\n\nAhead on:\n- Security \u0026 auth, 79 against 55\n- Maintenance \u0026 community, 80 against 72\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n\n## Why the edge\n\n### Reliability: Cohere Chat API (Command models) +42\n\n- Cohere Chat API (Command models) (67): Hosted lines. status.cohere.com (incident.io) lists each Command model and the endpoints as components (20). Its feed, read on 2 November 2026, shows two incidents in the 90 days from 4 August. 'Multiple Endpoint Disruptions' on 1 September 2026, from 15:41 to 19:47 UTC, degraded the embeddings endpoint, embed-v4.0, two rerank models and `command-a-reasoning-08-2025` during a Google Cloud outage, rated minor and partial, and docs loading failed on 5 August. Nothing has been posted since 1 September, so minor incidents only (20). Chat limits are published per model, 20 requests a minute and 1,000 calls a month on a trial key and 500 a minute on a production key for Command A, R, R+ and R7B, while the four newest variants say contact sales (12 of 15). The errors page documents 429 with example messages that say to wait and try again later and links to the rate limits, with no Retry-After header, backoff timing or idempotency key, the reading cohere-embed takes of the same page (8 of 15). cohere.com/slo is titled Service Level Objective and its text is script-drawn, so it was unread and scores as absent (0). The v2 chat endpoint is the default docs version, but the sample response on the chat guide still carries `is_experimental` and the newest models are not open to production keys (7 of 10).\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n\n### Security \u0026 auth: Hugging Face Inference Providers +24\n\n- Cohere Chat API (Command models) (55): Model reading. Bearer keys of two kinds, trial and production. Team roles are Owner and User, only Owners delete production keys, and a production key is shown in full once. No scopes, expiry or per-model restriction was found (18 of 30). Paying customers can switch training off under Data Controls, which implies it is on until they do, trial keys fall under the website terms, and the SaaS agreement grants an irrevocable right to use API data to improve the services and share it with third parties (8 of 20). Logged prompts and generations are deleted after 30 days unless flagged, and zero data retention needs approval (12 of 15). The dashboard shows usage history, and no customer audit log was found (2 of 15). The trust centre lists SOC 2 Type II, ISO 27001, ISO 42001, UK Cyber Essentials, penetration tests on request and a responsible disclosure policy with a bug bounty, per the 9 October check. cohere.com/.well-known/security.txt still answers 404 on 2 November and no public advisories were found, so the line takes 15, as cohere-embed and cohere-north read the same programme (15 of 20).\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n\n### Schema \u0026 documentation: Cohere Chat API (Command models) +22\n\n- Cohere Chat API (Command models) (84): Model reading. Public OpenAPI 3.1 file `cohere-openapi.yaml` in cohere-ai/cohere-developer-experience, 43 operations, last changed 29 September 2026 (25). docs.cohere.com/llms.txt and a Markdown twin of every page by adding `.md`, though the llms.txt files list no pages (8 of 10). The v2 chat operation describes each of its 21 request fields with defaults and limits, and says less about when to prefer one option (16 of 20). Enums on `tool_choice`, `safety_mode` and `thinking.type`, numeric bounds on `temperature`, `k`, `p` and `priority`, with penalties bounded only in prose (12 of 15). Eight request examples on the operation and an errors page with sample messages for each status code, with error bodies carrying a message and no machine code (12 of 15). v1 and v2 live side by side in the path and the changelog is dated, but the OpenAPI file is version 1.0 throughout and its changes are committed as 'Add spec changes' with no per-change note (11 of 15).\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n\n### Payments \u0026 pricing: Cohere Chat API (Command models) +15\n\n- Cohere Chat API (Command models) (35): No x402, MPP or L402 in the docs, the OpenAPI file or the pricing page (0). The docs say Command models are billed per input and output token. The pricing page, read on 2 November 2026, now carries per-unit prices in its own page data, Command R at $0.15 input and $0.60 output and Command R7B at $0.0375 and $0.15 per million tokens, with Command R+ 08-2024 at $2.50 and $10.00 among legacy prices and Command A+ shown as free. No price is published for Command A, Reasoning, Vision or Translate, so the line takes 15 rather than the full 20 (15 of 20). A trial key is created at sign-up and is free with no card (20). Sign-up is in a browser, and a production key needs an Owner to complete a Go to Production form (0).\n- Hugging Face Inference Providers (20): No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).\n\n### Agent ergonomics: Cohere Chat API (Command models) +14\n\n- Cohere Chat API (Command models) (72): Model reading. Function calling with `tool_choice` REQUIRED or NONE and `strict_tools`, which the reference marks beta (17 of 20). `response_format` takes `json_object` or a JSON Schema, with limits documented and no support in RAG mode (13 of 15). The usage object reports `cached_tokens`, and no guide or price for prompt caching was found (5 of 15). Context is 256,000 tokens on Command A and Command A Reasoning and 128,000 on Command A+ (10 of 15). `/v2/batches` runs a batch from an uploaded dataset, with no price or discount found (6 of 10). Official SDKs for Python, TypeScript, Java and Go (10). Error messages are specific and readable, with no stable error codes (11 of 15).\n- Hugging Face Inference Providers (58): Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +8\n\n- Cohere Chat API (Command models) (72): Model reading. The last dated release on the Chat endpoint is still North Small Translate on 9 September 2026, 54 days before this check. The last Command model is Command A+ on 20 May 2026. Rerank 5 (21 October) and Embed 5 (30 September) aren't chat changes, so we score the 90-day band (20 of 30). The deprecations page defines Active, Legacy, Deprecated and Shutdown and promises email notice, with no minimum notice period (6 of 12). No chat model was retired or announced for retirement in the last 90 days. The newest entry on the page is still two Aya models retired on 4 April 2026 (8 of 8). Dated changelog with four entries since 4 August (27 August, 9 September, 30 September, 21 October), one of them for a chat model (12 of 15). SDK issue replies not sampled (5 of 10). Python SDK 7.2.0 and 7.3.0, TypeScript 8.2.0 (19 October) and 8.3.0, and Go v2.20.0 tagged on 21 October 2026, Java at 1.12.0 (15). The Python SDK is generated from the OpenAPI file and has a CI workflow, whose runs we did not read (6 of 10).\n- Hugging Face Inference Providers (80): Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).\n\n## Score by category\n\n| Category | Weight | Cohere Chat API (Command models) | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 67 | 25 | Cohere Chat API (Command models) +42 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 84 | 62 | Cohere Chat API (Command models) +22 |\n| Agent ergonomics | 13% (16.2 this run) | 72 | 58 | Cohere Chat API (Command models) +14 |\n| Security \u0026 auth | 14% (17.5 this run) | 55 | 79 | Hugging Face Inference Providers +24 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 35 | 20 | Cohere Chat API (Command models) +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 72 | 80 | Hugging Face Inference Providers +8 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 75 | 71 | Cohere Chat API (Command models) +4 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.6 · B** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | Cohere Chat API (Command models) | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Cohere | Hugging Face, Inc. |\n| Hosted endpoint | `https://api.cohere.com/v2/chat` | `https://router.huggingface.co/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under Cohere's Commercial SaaS Agreement. The SDKs are MIT | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-09 | 2026-10-29 |\n| Terms last updated | 2025-04-08 | 2022-09-15 |\n| Privacy policy last updated | 2026-05-01 | 2023-03-28 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | yes | yes |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | none | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Cohere Chat API (Command models)\n\n- +0.9 on 2 November 2026: new evidence, correction\n- no change on 28 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Cohere Chat API (Command models).** A public OpenAPI file, Markdown twins of every docs page and SDKs in four languages make the Chat API easy for an agent to read. Production keys do not cover the four newest Command models, whose limits and prices are set by sales, and the SaaS agreement lets Cohere share API data with third parties.\n\n**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.\n\n## Before you call either\n\n### Cohere Chat API (Command models)\n\n1. Call `POST https://api.cohere.com/v2/chat` with `Authorization: bearer \u003ckey\u003e`. `model` and `messages` are the only required fields\n2. Use `command-a-03-2025`, `command-r-08-2024`, `command-r-plus-08-2024` or `command-r7b-12-2024` for production traffic. Newer variants stay at trial limits on a production key, and only the R models have published prices\n3. Keep a trial key under 20 chat requests a minute and 1,000 calls a month, and do not use it for commercial work\n4. Set `response_format` with a `json_schema` for structured output, and tell the model to produce JSON when using `json_object` without a schema\n5. Ask the account Owner to turn off training under Data Controls in the dashboard before sending confidential prompts\n\n### Hugging Face Inference Providers\n\n1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider\n2. Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider\n3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation\n4. Back off on 429 without assuming a Retry-After header, since none is documented for the router\n\n## Questions\n\n### Which is better for AI agents, Cohere Chat API (Command models) or Hugging Face Inference Providers?\n\nCohere Chat API (Command models) scores 65.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 5 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth and maintenance \u0026 community.\n\n### Do Cohere Chat API (Command models) and Hugging Face Inference Providers need an API key?\n\nBoth need an API key.\n\n### Can an agent call Cohere Chat API (Command models) and Hugging Face Inference Providers without installing anything?\n\nYes. Cohere Chat API (Command models) has a hosted endpoint at https://api.cohere.com/v2/chat and Hugging Face Inference Providers at https://router.huggingface.co/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cohere-chat\", \"b\": \"hugging-face-inference-providers\"}`. 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