{ "data": { "a": { "slug": "meta-model-api", "name": "Meta Model API", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Meta Model API is Meta's pay-as-you-go API for its hosted Muse models, including Muse Wonder and Muse Spark, through OpenAI-style Responses and Chat Completions endpoints and an Anthropic-style Messages endpoint, plus image, speech and segmentation routes.", "url": "https://www.anchorterminal.com/tools/meta-model-api", "markdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/meta-model-api.json", "license": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "transports": [ "http" ], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer API key created on the API keys tab of the Model API dashboard after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team, are shown once and are revoked by deletion. No key scopes were found, and every key on a team shares the team's rate limits.", "pricing": "usage", "pricingNotes": "Muse Wonder is $4.00 per million input tokens, $0.20 cached and $20.00 per million output tokens, Standard mode only (checked 2026-10-12). Muse Spark is $1.25, $0.15 and $4.25, or $0.10, $0.002 and $0.20 in Contributor mode, where Meta may train on the content. Billed in arrears to a card. No free allowance was found.", "priceSummary": "$2.50 / 1k req", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in dev.meta.ai/llms.txt, the pricing page, the API reference or the billing help pages, checked 12 October 2026. Usage is charged to a card at a payment threshold or on the 1st of each month.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-12" }, "docsUrl": "https://dev.meta.ai/docs/overview", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "image.generate", "image.edit", "speech.stt", "speech.streaming" ], "tags": [ "official", "hosted", "model", "usage-priced", "closed-source", "llms-txt", "multimodal", "streaming", "openai-compatible", "anthropic-compatible", "card-required" ], "lastRelease": "2026-10-12", "graded": true, "anchor": { "graded": true, "score": 52.2, "grade": "D", "agentReady": false, "rank": 757, "ranked": true, "rankOf": 993, "categoryRank": 16, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-12" }, "negative": 0, "verdict": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "bestFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "strengths": [ "Muse Wonder and Muse Spark take text, image, video, audio and PDF input with a 1,048,576-token context window", "Per-token prices, per-model rate limits and rate-limit headers published without a login", "Content sent in Standard mode is not used to train Meta models, and training use is opt-in through `-contributor` model IDs", "Responses, Chat Completions and Messages endpoints, so the OpenAI and Anthropic SDKs work with a base-URL change", "llms.txt and a Markdown copy of every docs page, with an error guide that gives the Retry-After value for each retryable error" ], "weaknesses": [ "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found", "No free API allowance found, and billing is set up with a card", "No status page with history. The docs' status link redirects to the home page, and `/v1/status` reports only the current state", "`tool_choice` accepts only `auto`, so a call can't be forced or ruled out", "No OpenAPI file, batch endpoint or Model API changelog found, and API keys have no scopes" ], "agentNotes": [ "Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests", "Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content", "Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key", "Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`", "Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.2 } ], "editorialScores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 63 }, "connect": { "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"muse-spark-1.3\", \"input\": \"What is the capital of France?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/meta-model-api" }, "sameCompany": [ "muse-code" ], "area": "models", "unitPrices": [ { "item": "Muse Wonder input", "unit": "1m-tokens", "usd": 4, "note": "Standard mode, muse-wonder-1.0. No long-context premium." }, { "item": "Muse Wonder cached input", "unit": "1m-tokens", "usd": 0.2 }, { "item": "Muse Wonder output", "unit": "1m-tokens", "usd": 20 }, { "item": "Muse Spark input", "unit": "1m-tokens", "usd": 1.25, "note": "Standard mode, muse-spark-1.3, 1.2 and 1.1." }, { "item": "Muse Spark cached input", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Muse Spark output", "unit": "1m-tokens", "usd": 4.25 }, { "item": "Muse Spark input, Contributor mode", "unit": "1m-tokens", "usd": 0.1, "note": "Meta may use the content to train its models." }, { "item": "Muse Spark output, Contributor mode", "unit": "1m-tokens", "usd": 0.2, "note": "Cached input is $0.002 per million tokens." }, { "item": "Web search grounding", "unit": "1k-requests", "usd": 2.5, "note": "Per 1,000 search queries, on top of token cost." }, { "item": "Muse Image generated image", "unit": "image", "usd": 0.01 } ], "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://dev.meta.ai/legal/terms-of-service", "privacy": "https://www.facebook.com/privacy/policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-12", "notes": [ "The terms (last updated 9 October 2026) are an agreement with Meta Platforms, Inc., or Meta Platforms Ireland Limited for users in the European Region. The model card names the same two.", "The privacy field is the Meta Privacy Policy, which the terms link. www.facebook.com's robots.txt asks readers like ours not to fetch it, as the 8 October policy reading records, so it wasn't read. The terms also link a subprocessor list at forwork.meta.com/legal/mfw-subprocessor-list/ and the Meta Global Processor Terms, neither of which was read.", "RDAP for meta.ai gives a registration date of 16 December 2017. The API answers at api.meta.ai.", "No status page. The error guide links dev.meta.ai/status, which redirects to the home page. `GET /v1/status` is an unauthenticated health endpoint with no history.", "No Model API changelog was found. The only changelog on dev.meta.ai is Muse Code's.", "dev.meta.ai/.well-known/security.txt returns 404. www.meta.ai's robots.txt disallows ClaudeBot, so its security.txt wasn't requested. www.facebook.com/.well-known/security.txt is valid until 11 November 2026 and points to bugbounty.meta.com.", "developer.meta.com/ai/ redirects to dev.meta.ai." ], "score": 63 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/meta-model-api.json", "live": { "slug": "meta-model-api", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-10-12T22:35:32.230718004Z", "lastOk": true, "lastStatus": 404, "lastMs": 115, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 87, "p95ms24h": 166, "samples24h": 19, "samples30d": 19, "days": [ { "date": "2026-10-12", "probes": 19, "ok": 19 } ] }, "updatedAt": "2026-10-12T22:35:32.230718004Z" } }, "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category.", "b": { "slug": "mistral-api", "name": "Mistral AI API", "vendor": "Mistral AI", "vendorUrl": "https://mistral.ai", "kind": "model", "category": "inference", "summary": "Mistral's API for its open-weight and proprietary models, with EU and US regional endpoints.", "url": "https://www.anchorterminal.com/tools/mistral-api", "markdownUrl": "https://www.anchorterminal.com/tools/mistral-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mistral-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mistral-api.json", "repo": "https://github.com/mistralai/client-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.mistral.ai/v1", "packages": [ { "registry": "pypi", "name": "mistralai" }, { "registry": "npm", "name": "@mistralai/mistralai" } ], "auth": "api-key", "authNotes": "Bearer key. Regional EU and US endpoints are opt-in.", "pricing": "freemium", "pricingNotes": "Free Experiment tier with no card, but a phone number, and its data may be used for training. Cached input 10% of the input price, batch half price, regional endpoints 1.1x. Mistral Large 4 (preview) is $1.36/$4.18 per million tokens, cached input $0.14, at half price for two weeks from its 6 October launch. Also resells Z.ai GLM 5.3 at $1.40/$4.40 (https://mistral.ai/pricing/api/).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 769, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://docs.mistral.ai", "rateLimitsUrl": "https://docs.mistral.ai/admin/user-management-finops/tier", "llmsTxt": "https://docs.mistral.ai/llms.txt", "openapi": "https://docs.mistral.ai/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "eu", "open-weights", "free-tier", "openapi", "llms-txt" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 71.2, "grade": "BB", "agentReady": true, "rank": 134, "ranked": true, "rankOf": 993, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 91, "maintenance": 88, "payments": 40, "reliability": 50, "schema": 93, "security": 66, "transparency": 80 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-12" }, "negative": 0, "verdict": "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.", "bestFor": "Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.", "strengths": [ "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins", "Minimum 6 months' notice before a GA model retires, and retired ids return 404", "Workspace-scoped API keys with expiry dates, and service accounts bound to workspace roles", "Opt-in EU and US regional endpoints, at 1.1x", "Free Experiment tier with no card, and Batch at half price" ], "weaknesses": [ "Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting", "The terms don't say whether the paid API trains by default", "Labs, preview and third-party models get only 1 month's notice", "Rate-limit numbers are only in the console, and no SLA found", "17 Completion, Conversations and Batch API incidents on the status page in August 2026, and an elevated error rate for 2 hours 40 minutes on 29 September" ], "agentNotes": [ "Stay off `labs-*` and preview models, `mistral-large-4` included while it is in preview, for anything confidential", "Use the EU endpoint when data has to stay in Europe and budget the 10% uplift", "Treat a 404 on a model id as retirement and read the lifecycle page for the replacement", "Set `tool_choice` to any to force a tool call, and `strict` on the JSON schema for structured output", "Read docs.mistral.ai/openapi.yaml for the request shapes instead of guessing from OpenAI's" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 4, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 71.2 } ], "editorialScores": { "ergonomics": 91, "maintenance": 88, "payments": 40, "reliability": 50, "schema": 93, "security": 66, "transparency": 68 }, "provenanceScore": 91 }, "connect": { "install": "pip install mistralai # or: npm i @mistralai/mistralai", "http": "curl https://api.mistral.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $MISTRAL_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"mistral-medium-3-5\",\"messages\":[{\"role\":\"user\",\"content\":\"bonjour\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/mistral-api" }, "sameCompany": [ "mistral-embeddings", "mistral-moderation", "mistral-voxtral-transcribe", "mistral-ocr" ], "area": "models", "provenance": { "legalEntity": "Mistral AI (RCS Paris 952 418 325)", "domain": "mistral.ai", "domainRegistered": "2019-05-15", "endpointOnVendorDomain": true, "terms": "https://legal.mistral.ai/terms/commercial-terms-of-service", "privacy": "https://legal.mistral.ai/terms/privacy-policy", "statusPage": "https://status.mistral.ai", "changelog": "https://docs.mistral.ai/resources/changelogs", "securityTxt": "valid", "checked": "2026-09-26", "score": 91 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mistral-api.json", "live": { "slug": "mistral-api", "probe": { "target": "https://api.mistral.ai/v1", "method": "get", "lastAt": "2026-10-12T22:35:32.849853995Z", "lastOk": true, "lastStatus": 404, "lastMs": 66, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 70, "p95ms24h": 115, "samples24h": 248, "samples30d": 4117, "days": [ { "date": "2026-09-27", "probes": 132, "ok": 132 }, { "date": "2026-09-28", "probes": 285, "ok": 285 }, { "date": "2026-09-29", "probes": 286, "ok": 286 }, { "date": "2026-09-30", "probes": 286, "ok": 286 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 233, "ok": 233 } ] }, "vendorStatus": { "page": "https://status.mistral.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-12T21:47:18.752709908Z" }, "versions": [ { "registry": "github", "name": "mistralai/client-python", "version": "v3.2.0", "released": "2026-10-09", "seenAt": "2026-10-12T22:15:04.350054705Z" }, { "registry": "npm", "name": "@mistralai/mistralai", "version": "2.7.0", "seenAt": "2026-10-12T22:15:03.455739468Z" }, { "registry": "pypi", "name": "mistralai", "version": "3.2.0", "released": "2026-10-09", "seenAt": "2026-10-12T22:15:03.34664025Z" } ], "githubStars": 773, "npmWeekly": 7629786, "pypiWeekly": 3096752, "securityTxt": { "url": "https://mistral.ai/.well-known/security.txt", "state": "valid", "expires": "2027-05-05T23:59:59.000Z", "checkedAt": "2026-10-12T15:44:40.262883783Z" }, "llmsTxt": { "url": "https://docs.mistral.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-12T14:09:29.563175461Z" }, "domain": { "domain": "mistral.ai", "registered": "2019-05-15", "source": "https://rdap.identitydigital.services/rdap/domain/mistral.ai", "checkedAt": "2026-10-11T13:13:49.820537908Z" }, "pages": [ { "url": "https://docs.mistral.ai/resources/changelogs", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-12T19:50:33.60836241Z", "changedAt": "2026-10-07T18:05:15.998003428Z", "fingerprint": "f37008aff154" }, { "url": "https://legal.mistral.ai/terms/commercial-terms-of-service", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-12T19:54:01.634854826Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "227daf1e9929" }, { "url": "https://mistral.ai/pricing/api/", "kind": "pricing", "status": 200, "checkedAt": "2026-10-12T19:54:56.864289725Z", "changedAt": "2026-10-07T18:07:31.904425325Z", "fingerprint": "a7cad481f8de" }, { "url": "https://legal.mistral.ai/terms/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-12T19:54:04.01428827Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e74211012ef6" } ], "models": { "ministral-3b-2512": { "openrouterId": "mistralai/ministral-3b-2512", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 131072, "maxOutput": 104857, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "mistral-large-2512": { "openrouterId": "mistralai/mistral-large-2512", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": false, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "mistral-medium-3-5": { "openrouterId": "mistralai/mistral-medium-3-5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": false, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "mistral-small-2603": { "openrouterId": "mistralai/mistral-small-2603", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 262144, "maxOutput": 209715, "checkedAt": "2026-10-11T22:59:28.731564938Z" } }, "updatedAt": "2026-10-12T22:35:32.849853995Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Meta", "b": "Mistral AI", "name": "Vendor" }, { "a": "https://api.meta.ai/v1", "b": "https://api.mistral.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "b": "Apache-2.0 (SDKs)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-12", "b": "2026-10-06", "name": "Last release" }, { "a": "", "b": "2026-09-25", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "2026-09-03", "name": "Privacy policy last updated" }, { "a": "", "b": "yes, with an opt-out", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "769 stars", "name": "Popularity" }, { "a": "none", "b": "4/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Mistral AI API scores 71.2 (BB) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category.", "question": "Which is better for AI agents, Meta Model API or Mistral AI API?" }, { "answer": "Both need an API key.", "question": "Do Meta Model API and Mistral AI API need an API key?" }, { "answer": "Yes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and Mistral AI API at https://api.mistral.ai/v1.", "question": "Can an agent call Meta Model API and Mistral AI API without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "slug": "meta-model-api", "watchFor": "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found" }, { "aheadOn": [ "Reliability, 50 against 40", "Schema \u0026 documentation, 93 against 60", "Agent ergonomics, 91 against 75", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 88 against 46", "Transparency \u0026 trust, 80 against 52" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.", "slug": "mistral-api", "watchFor": "Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json", "title": "Claude API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.json", "title": "Claude API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.json", "title": "Antseed vs Meta Model API", "url": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-mistral-api.json", "title": "Antseed vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/antseed-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.json", "title": "BlockRun.AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.json", "title": "BlockRun.AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.json", "title": "Cloudflare AI Gateway vs Meta Model API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-mistral-api.json", "title": "Cloudflare AI Gateway vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.json", "title": "Cloudflare Workers AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-mistral-api.json", "title": "Cloudflare Workers AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-mistral-api" }, { "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-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/deepinfra-vs-meta-model-api.json", "title": "DeepInfra vs Meta Model API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-mistral-api.json", "title": "DeepInfra vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json", "title": "DeepSeek API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.json", "title": "DeepSeek API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.json", "title": "Gemini Developer API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api.json", "title": "Gemini Developer API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json", "title": "GroqCloud vs Meta Model API", "url": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-mistral-api.json", "title": "GroqCloud vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/groq-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.json", "title": "Meta Model API vs Novita AI", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "title": "Meta Model API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.json", "title": "Meta Model API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.json", "title": "Meta Model API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json", "title": "Meta Model API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json", "title": "Meta Model API vs StepFun API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai.json", "title": "Mistral AI API vs Novita AI", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.json", "title": "Mistral AI API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openrouter.json", "title": "Mistral AI API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.json", "title": "Mistral AI API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json", "title": "Mistral AI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.json", "title": "Mistral AI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.json", "title": "Mistral AI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api" } ], "scores": [ { "by": 10, "edge": "mistral-api", "key": "reliability", "meta-model-api": 40, "mistral-api": 50, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 33, "edge": "mistral-api", "key": "schema", "meta-model-api": 60, "mistral-api": 93, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 16, "edge": "mistral-api", "key": "ergonomics", "meta-model-api": 75, "mistral-api": 91, "name": "Agent ergonomics", "weight": 13 }, { "by": 2, "edge": "mistral-api", "key": "security", "meta-model-api": 64, "mistral-api": 66, "name": "Security \u0026 auth", "weight": 14 }, { "by": 20, "edge": "mistral-api", "key": "payments", "meta-model-api": 20, "mistral-api": 40, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 42, "edge": "mistral-api", "key": "maintenance", "meta-model-api": 46, "mistral-api": 88, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 28, "edge": "mistral-api", "key": "transparency", "meta-model-api": 52, "mistral-api": 80, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Mistral AI API scores 71.2 (BB) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category. Both do llm inference.", "verdicts": { "meta-model-api": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "mistral-api": "Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api", "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.md", "slim": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.min.md" }, "markdown": "Mistral AI API scores 71.2 (BB) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category. Both do llm inference.\n\n- Meta Model API: grade D, 52.2/100, rank #757 of 993. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- Mistral AI API: grade BB, 71.2/100, rank #134 of 993. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 171 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Meta Model API (D)\n\nGood for: Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\n\n### Mistral AI API (BB)\n\nGood for: Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.\n\nAhead on:\n- Reliability, 50 against 40\n- Schema \u0026 documentation, 93 against 60\n- Agent ergonomics, 91 against 75\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 88 against 46\n- Transparency \u0026 trust, 80 against 52\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting\n\n\n## Score by category\n\n| Category | Weight | Meta Model API | Mistral AI API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 50 | Mistral AI API +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 93 | Mistral AI API +33 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 91 | Mistral AI API +16 |\n| Security \u0026 auth | 14% (17.5 this run) | 64 | 66 | Mistral AI API +2 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | Mistral AI API +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 88 | Mistral AI API +42 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 52 | 80 | Mistral AI API +28 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **52.2 · D** | **71.2 · BB** | |\n\n## Facts side by side\n\n| Fact | Meta Model API | Mistral AI API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | Mistral AI |\n| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.mistral.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party. | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-12 | 2026-10-06 |\n| Terms last updated | | 2026-09-25 |\n| Privacy policy last updated | couldn't be read | 2026-09-03 |\n| Customer content may train models | | yes, with an opt-out |\n| Terms restrict automated access | | not found in the text |\n| Terms restrict benchmarking | | yes |\n| Terms or service can change without notice | | yes |\n| Arbitration or class-action waiver | | not found in the text |\n| Popularity | none | 769 stars |\n| Agent reviews | none | 4/5 (2) |\n\n## Verdicts\n\n**Meta Model API.** Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.\n\n**Mistral AI API.** Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them since 6 October, may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.\n\n## Before you call either\n\n### Meta Model API\n\n1. Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests\n2. Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content\n3. Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key\n4. Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`\n5. Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported\n\n### Mistral AI API\n\n1. Stay off `labs-*` and preview models, `mistral-large-4` included while it is in preview, for anything confidential\n2. Use the EU endpoint when data has to stay in Europe and budget the 10% uplift\n3. Treat a 404 on a model id as retirement and read the lifecycle page for the replacement\n4. Set `tool_choice` to any to force a tool call, and `strict` on the JSON schema for structured output\n5. Read docs.mistral.ai/openapi.yaml for the request shapes instead of guessing from OpenAI's\n\n## Questions\n\n### Which is better for AI agents, Meta Model API or Mistral AI API?\n\nMistral AI API scores 71.2 (BB) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category.\n\n### Do Meta Model API and Mistral AI API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Meta Model API and Mistral AI API without installing anything?\n\nYes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and Mistral AI API at https://api.mistral.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"meta-model-api\", \"b\": \"mistral-api\"}`. From a terminal: `anchor compare meta-model-api mistral-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/meta-model-api.json and https://www.anchorterminal.com/api/v1/tools/mistral-api.json\n\n## Other comparisons with Meta Model API or Mistral AI API\n\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Antseed vs Mistral AI API](https://www.anchorterminal.com/compare/antseed-vs-mistral-api.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [BlockRun.AI vs Mistral AI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.md)\n- [Cloudflare AI Gateway vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.md)\n- [Cloudflare AI Gateway vs Mistral AI API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-mistral-api.md)\n- [Cloudflare Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.md)\n- [Cloudflare Workers AI vs Mistral AI API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-mistral-api.md)\n- [Cohere Chat API (Command models) vs Meta Model API](https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.md)\n- [Cohere Chat API (Command models) vs Mistral AI API](https://www.anchorterminal.com/compare/cohere-chat-vs-mistral-api.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepInfra vs Mistral AI API](https://www.anchorterminal.com/compare/deepinfra-vs-mistral-api.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [Gemini Developer API vs Mistral AI API](https://www.anchorterminal.com/compare/gemini-api-vs-mistral-api.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [GroqCloud vs Mistral AI API](https://www.anchorterminal.com/compare/groq-vs-mistral-api.md)\n- [Meta Model API vs Novita AI](https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.md)\n- [Meta Model API vs OpenAI API](https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.md)\n- [Meta Model API vs OpenRouter](https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.md)\n- [Meta Model API vs Prism Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n- [Mistral AI API vs Novita AI](https://www.anchorterminal.com/compare/mistral-api-vs-novita-ai.md)\n- [Mistral AI API vs OpenAI API](https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.md)\n- [Mistral AI API vs OpenRouter](https://www.anchorterminal.com/compare/mistral-api-vs-openrouter.md)\n- [Mistral AI API vs Prism Inference](https://www.anchorterminal.com/compare/mistral-api-vs-prism-inference.md)\n- [Mistral AI API vs SambaCloud](https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.md)\n- [Mistral AI API vs SiliconFlow](https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.md)\n- [Mistral AI API vs StepFun API](https://www.anchorterminal.com/compare/mistral-api-vs-stepfun-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-12", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Meta Model API vs Mistral AI API", "url": "" } ], "description": "Mistral AI scores 71.2 (BB) to Meta Model's 52.2 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Meta Model API D 52.2", "Mistral AI API BB 71.2", "scores" ], "h1": "Meta Model API vs Mistral AI API", "image": "https://www.anchorterminal.com/assets/og/compare-meta-model-api-vs-mistral-api.png", "path": "/compare/meta-model-api-vs-mistral-api", "published": "2026-10-01", "section": "tools", "title": "Meta Model vs Mistral AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-12", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api" }, "tokens": { "markdown": 2750, "slim": 680 }, "version": 1 }