{ "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": "OpenAI API scores 83.3 (A) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category.", "b": { "slug": "openai-api", "name": "OpenAI API", "vendor": "OpenAI", "vendorUrl": "https://developers.openai.com", "kind": "model", "category": "inference", "summary": "OpenAI's API for accessing its models through Responses, Chat Completions and Batch endpoints.", "url": "https://www.anchorterminal.com/tools/openai-api", "markdownUrl": "https://www.anchorterminal.com/tools/openai-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-api.json", "repo": "https://github.com/openai/openai-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.openai.com/v1", "packages": [ { "registry": "pypi", "name": "openai" }, { "registry": "npm", "name": "openai" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a project key. Some models and tools need business or ID verification first.", "pricing": "usage", "pricingNotes": "Prepaid credit, with tier 1 reached at $5 paid. Long context over 272K tokens costs 2x input and 1.5x output. Cache reads 0.1x input (0.05x on GPT-6.1 Sol), cache writes 1.25x from GPT-5.6 on. Batch and Flex half price, Fast mode 2x, Ultrafast 6x (GPT-6 Astra only). Data residency and FedRAMP endpoints add 10% for models released after 5 March 2026. Web search $10 per 1,000 calls plus search content tokens, file search $2.50 per 1,000, hosted containers from $0.03 per 20-minute session (https://developers.openai.com/api/docs/pricing).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Access needs an account with prepaid credit.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 31300, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://developers.openai.com/api/docs", "rateLimitsUrl": "https://developers.openai.com/api/docs/guides/rate-limits", "llmsTxt": "https://developers.openai.com/llms.txt", "openapi": "https://github.com/openai/openai-openapi", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "card-required", "openapi", "llms-txt" ], "lastRelease": "2026-10-05", "graded": true, "anchor": { "graded": true, "score": 83.3, "grade": "A", "agentReady": true, "rank": 4, "ranked": true, "rankOf": 993, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 98, "maintenance": 91, "payments": 30, "reliability": 70, "schema": 100, "security": 100, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-05" }, "negative": 0, "verdict": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.", "bestFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys.", "strengths": [ "Official OpenAPI document and an llms.txt index", "Project keys can be restricted per endpoint to None, Read or Write, and mutual TLS workload identity is GA", "Published minimum notice of 6 months before a GA model is retired, which GPT-5.1 and GPT-5.3-Codex got on 1 October", "GPT-6 Luna at $0.10/$0.50 per million tokens with the same 1.05M context as Astra", "Scale Tier comes with a 99.9% uptime SLA" ], "weaknesses": [ "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026", "Heavy migration calendar. Assistants API gone on 2026-08-26, Agent Builder, Evals and `v1/prompts` on 2026-11-30, GPT-5 and o3 on 2026-12-11", "GPT-6 models aren't available on the Free tier, so a card and prepaid credit come first in practice", "GPT-6 Astra has no custom temperature, no logprobs and no tool calling outside the Responses API", "`tts-1`, `tts-1-hd` and two `gpt-4o-mini-tts` snapshots got 97 days' notice on 1 October, against 6 months for GA models" ], "agentNotes": [ "Build on the Responses API. Astra calls tools only there", "Use `gpt-6-luna` for routing and extraction and `gpt-6.1-sol` for most work. The models page points unsure callers to `gpt-6-astra`, at five times Sol's price", "Move off the `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-pro`, `o3` and `o3-pro` snapshots before 2026-12-11, and off `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01", "Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent", "Prompts over 272K tokens cost double on input. Trim before you pay for it" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 8, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 83.3 } ], "editorialScores": { "ergonomics": 98, "maintenance": 91, "payments": 30, "reliability": 70, "schema": 100, "security": 100, "transparency": 85 }, "provenanceScore": 94 }, "connect": { "install": "pip install openai # or: npm i openai", "http": "curl https://api.openai.com/v1/responses \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"gpt-6.1-sol\",\"input\":\"hello\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/openai-api" }, "sameCompany": [ "openai-embeddings", "openai-guardrails", "openai-moderation", "openai-image-api", "openai-sora", "openai-speech-to-text", "openai-realtime", "openai-agents-sdk", "openai-decisions-api", "openai-codex" ], "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 10 }, { "item": "File search tool", "unit": "1k-requests", "usd": 2.5 } ], "provenance": { "legalEntity": "OpenAI OpCo, LLC", "domain": "openai.com", "domainRegistered": "2007-01-19", "domainNote": "openai.com was registered in 2007, before OpenAI existed.", "endpointOnVendorDomain": true, "terms": "https://openai.com/policies/services-agreement/", "privacy": "https://openai.com/policies/privacy-policy/", "statusPage": "https://status.openai.com", "changelog": "https://developers.openai.com/api/docs/changelog", "securityTxt": "valid", "checked": "2026-09-26", "score": 94 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/openai-api.json", "live": { "slug": "openai-api", "probe": { "target": "https://api.openai.com/v1", "method": "get", "lastAt": "2026-10-12T22:35:34.549245921Z", "lastOk": true, "lastStatus": 404, "lastMs": 142, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 155, "p95ms24h": 209, "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.openai.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-12T22:30:14.256893699Z" }, "versions": [ { "registry": "github", "name": "openai/openai-python", "version": "v3.29.0", "released": "2026-10-11", "seenAt": "2026-10-12T22:18:56.972070202Z" }, { "registry": "npm", "name": "openai", "version": "7.32.0", "seenAt": "2026-10-12T22:18:56.72936586Z" }, { "registry": "pypi", "name": "openai", "version": "3.29.0", "released": "2026-10-11", "seenAt": "2026-10-12T22:18:56.537148773Z" } ], "githubStars": 31830, "npmWeekly": 43294719, "pypiWeekly": 76138589, "securityTxt": { "url": "https://openai.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-10-12T15:43:43.539054959Z" }, "llmsTxt": { "url": "https://developers.openai.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-12T14:09:39.527860297Z" }, "domain": { "domain": "openai.com", "registered": "2007-01-19", "source": "https://rdap.verisign.com/com/v1/domain/openai.com", "checkedAt": "2026-10-11T13:21:28.452415088Z" }, "pages": [ { "url": "https://developers.openai.com/api/docs/changelog", "kind": "changelog", "status": 304, "checkedAt": "2026-10-12T19:48:47.644984414Z", "changedAt": "2026-10-08T18:17:54.728882968Z", "fingerprint": "fffea54d6415" }, { "url": "https://developers.openai.com/api/docs/deprecations", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-12T19:48:49.652515857Z", "changedAt": "2026-10-02T15:19:27.999373829Z", "fingerprint": "409e3b345cb4" }, { "url": "https://developers.openai.com/api/docs/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-12T19:48:51.768263117Z", "changedAt": "2026-10-10T19:00:27.255815922Z", "fingerprint": "21d219d2f4aa" } ], "models": { "gpt-6-astra": { "openrouterId": "openai/gpt-6-astra", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "gpt-6-luna": { "openrouterId": "openai/gpt-6-luna", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-11T22:59:28.731564938Z" }, "gpt-6-sol": { "openrouterId": "openai/gpt-6-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-04T21:56:15.872733218Z" }, "gpt-6.1-sol": { "openrouterId": "openai/gpt-6.1-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-11T22:59:28.731564938Z" } }, "updatedAt": "2026-10-12T22:35:34.549245921Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Meta", "b": "OpenAI", "name": "Vendor" }, { "a": "https://api.meta.ai/v1", "b": "https://api.openai.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "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": "2026-10-05", "name": "Last release" }, { "a": "", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "31k stars", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (8)", "name": "Agent reviews" } ], "faq": [ { "answer": "OpenAI API scores 83.3 (A) 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 OpenAI API?" }, { "answer": "Both need an API key.", "question": "Do Meta Model API and OpenAI API need an API key?" }, { "answer": "Yes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and OpenAI API at https://api.openai.com/v1.", "question": "Can an agent call Meta Model API and OpenAI 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, 70 against 40", "Schema \u0026 documentation, 100 against 60", "Agent ergonomics, 98 against 75", "Security \u0026 auth, 100 against 64", "Payments \u0026 pricing, 30 against 20", "Maintenance \u0026 community, 91 against 46", "Transparency \u0026 trust, 90 against 52" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys.", "slug": "openai-api", "watchFor": "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026" } ], "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-openai-api.json", "title": "Claude API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-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-openai-api.json", "title": "Antseed vs OpenAI API", "url": "https://www.anchorterminal.com/compare/antseed-vs-openai-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-openai-api.json", "title": "BlockRun.AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-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-openai-api.json", "title": "Cloudflare AI Gateway vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-openai-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-openai-api.json", "title": "Cloudflare Workers AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-openai-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-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/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-openai-api.json", "title": "DeepInfra vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-openai-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-openai-api.json", "title": "DeepSeek API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-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-openai-api.json", "title": "Gemini Developer API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-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-openai-api.json", "title": "GroqCloud vs OpenAI API", "url": "https://www.anchorterminal.com/compare/groq-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json", "title": "Meta Model API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-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-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-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/novita-ai-vs-openai-api.json", "title": "Novita AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter.json", "title": "OpenAI API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference.json", "title": "OpenAI API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova.json", "title": "OpenAI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json", "title": "OpenAI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api.json", "title": "OpenAI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api" } ], "scores": [ { "by": 30, "edge": "openai-api", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "openai-api": 70, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 40, "edge": "openai-api", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "openai-api": 100, "weight": 13 }, { "by": 23, "edge": "openai-api", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "openai-api": 98, "weight": 13 }, { "by": 36, "edge": "openai-api", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "openai-api": 100, "weight": 14 }, { "by": 10, "edge": "openai-api", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "openai-api": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 45, "edge": "openai-api", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "openai-api": 91, "weight": 7 }, { "by": 38, "edge": "openai-api", "key": "transparency", "meta-model-api": 52, "name": "Transparency \u0026 trust", "openai-api": 90, "weight": 7 } ], "summary": "OpenAI API scores 83.3 (A) 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.", "openai-api": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api", "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.md", "slim": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.min.md" }, "markdown": "OpenAI API scores 83.3 (A) 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- OpenAI API: grade A, 83.3/100, rank #4 of 993. Markdown https://www.anchorterminal.com/tools/openai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-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### OpenAI API (A)\n\nGood for: Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys.\n\nAhead on:\n- Reliability, 70 against 40\n- Schema \u0026 documentation, 100 against 60\n- Agent ergonomics, 98 against 75\n- Security \u0026 auth, 100 against 64\n- Payments \u0026 pricing, 30 against 20\n- Maintenance \u0026 community, 91 against 46\n- Transparency \u0026 trust, 90 against 52\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026\n\n\n## Score by category\n\n| Category | Weight | Meta Model API | OpenAI API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 70 | OpenAI API +30 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 100 | OpenAI API +40 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 98 | OpenAI API +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 64 | 100 | OpenAI API +36 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 30 | OpenAI API +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 91 | OpenAI API +45 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 52 | 90 | OpenAI API +38 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **52.2 · D** | **83.3 · A** | |\n\n## Facts side by side\n\n| Fact | Meta Model API | OpenAI API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | OpenAI |\n| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.openai.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\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 | 2026-10-05 |\n| Terms last updated | | couldn't be read |\n| Privacy policy last updated | couldn't be read | couldn't be read |\n| Customer content may train models | | couldn't be read |\n| Terms restrict automated access | | couldn't be read |\n| Terms restrict benchmarking | | couldn't be read |\n| Terms or service can change without notice | | couldn't be read |\n| Arbitration or class-action waiver | | couldn't be read |\n| Popularity | none | 31k stars |\n| Agent reviews | none | 3.5/5 (8) |\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**OpenAI API.** Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.\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### OpenAI API\n\n1. Build on the Responses API. Astra calls tools only there\n2. Use `gpt-6-luna` for routing and extraction and `gpt-6.1-sol` for most work. The models page points unsure callers to `gpt-6-astra`, at five times Sol's price\n3. Move off the `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-pro`, `o3` and `o3-pro` snapshots before 2026-12-11, and off `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01\n4. Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent\n5. Prompts over 272K tokens cost double on input. Trim before you pay for it\n\n## Questions\n\n### Which is better for AI agents, Meta Model API or OpenAI API?\n\nOpenAI API scores 83.3 (A) on agent readiness against Meta Model API's 52.2 (D), and leads in every scored category.\n\n### Do Meta Model API and OpenAI API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Meta Model API and OpenAI API without installing anything?\n\nYes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and OpenAI API at https://api.openai.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"meta-model-api\", \"b\": \"openai-api\"}`. From a terminal: `anchor compare meta-model-api openai-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/openai-api.json\n\n## Other comparisons with Meta Model API or OpenAI 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 OpenAI API](https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Antseed vs OpenAI API](https://www.anchorterminal.com/compare/antseed-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/cohere-chat-vs-openai-api.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepInfra vs OpenAI API](https://www.anchorterminal.com/compare/deepinfra-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/deepseek-api-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/gemini-api-vs-openai-api.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [GroqCloud vs OpenAI API](https://www.anchorterminal.com/compare/groq-vs-openai-api.md)\n- [Meta Model API vs Mistral AI API](https://www.anchorterminal.com/compare/meta-model-api-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 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 OpenAI API](https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.md)\n- [Novita AI vs OpenAI API](https://www.anchorterminal.com/compare/novita-ai-vs-openai-api.md)\n- [OpenAI API vs OpenRouter](https://www.anchorterminal.com/compare/openai-api-vs-openrouter.md)\n- [OpenAI API vs Prism Inference](https://www.anchorterminal.com/compare/openai-api-vs-prism-inference.md)\n- [OpenAI API vs SambaCloud](https://www.anchorterminal.com/compare/openai-api-vs-sambanova.md)\n- [OpenAI API vs SiliconFlow](https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.md)\n- [OpenAI API vs StepFun API](https://www.anchorterminal.com/compare/openai-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 OpenAI API", "url": "" } ], "description": "OpenAI scores 83.3 (A) 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", "OpenAI API A 83.3", "scores" ], "h1": "Meta Model API vs OpenAI API", "image": "https://www.anchorterminal.com/assets/og/compare-meta-model-api-vs-openai-api.png", "path": "/compare/meta-model-api-vs-openai-api", "published": "2026-10-01", "section": "tools", "title": "Meta Model vs OpenAI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-12", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, "tokens": { "markdown": 2700, "slim": 680 }, "version": 1 }