{ "data": { "a": { "slug": "claude-fable-5-2", "name": "Claude Fable 5.2", "vendor": "Anthropic", "vendorUrl": "https://www.anthropic.com", "kind": "model", "category": "inference", "summary": "Claude Fable 5.2 is Anthropic's most capable generally available model, for demanding reasoning and long-running agent work, with a 1M-token context, 128K output, text and images in, at $8 input and $40 output per million tokens.", "url": "https://www.anchorterminal.com/tools/claude-fable-5-2", "markdownUrl": "https://www.anchorterminal.com/tools/claude-fable-5-2.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/claude-fable-5-2.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/claude-fable-5-2.json", "dns": "claude-fable-5-2.grade.anchorterminal.com", "license": "Closed model, used through the Claude API and cloud platforms under Anthropic's Commercial Terms of Service", "transports": [], "remoteUrl": "https://api.anthropic.com/v1", "packages": [], "auth": "api-key", "authNotes": "A Claude API key from the Console, sent as `x-api-key` or a bearer token with `anthropic-version`, per the Claude API listing. Self-serve on the Claude API, and on Amazon Bedrock, Google Cloud, Microsoft Foundry and the Claude Platform on AWS under their own accounts.", "pricing": "usage", "pricingNotes": "$8 per million input tokens, $40 output, cache writes $10 (5 minutes) or $16 (1 hour), cache reads $0.20, batch at half price, fast mode $16 and $80. Requires 30-day retention. New users get a small amount of free credit, per the Claude API listing (checked 2026-11-09).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on Anthropic's pricing page, which bills tokens to a Console account (checked 2026-11-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-09" }, "docsUrl": "https://platform.claude.com/docs/en/models/fable-5-2/overview", "llmsTxt": "https://platform.claude.com/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "vision", "reasoning", "long-context", "tool-calling", "usage-priced", "card-required", "closed-source", "llms-txt", "new" ], "lastRelease": "2026-11-09", "graded": true, "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by an agent running on Claude, by the same published checklist as every other listing, from Anthropic's own pages and the Claude API listing's platform readings, with every judgement call written in the note. The panel reviews Anthropic's listings at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.", "anchor": { "graded": true, "score": 77.3, "grade": "BB", "agentReady": true, "rank": 35, "ranked": true, "rankOf": 1517, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 95, "maintenance": 91, "payments": 30, "reliability": 60, "schema": 90, "security": 92, "transparency": 85 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-09" }, "negative": 0, "verdict": "Anthropic's strongest generally available model, 20% cheaper than Fable 5.1 at $8 and $40 per million tokens, with large vendor-reported gains in coding and agent work and the Claude API's mature tooling. Thinking can't be turned off, tools can't be forced, and it requires 30-day retention.", "bestFor": "Agents doing long, hard work (large coding changes, multi-step research, computer use) that can pay frontier prices, accept 30-day retention and don't need to force a tool call.", "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by an agent running on Claude, by the same published checklist as every other listing, from Anthropic's own pages and the Claude API listing's platform readings, with every judgement call written in the note. The panel reviews Anthropic's listings at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.", "strengths": [ "$8 input and $40 output per million tokens, 20% below Fable 5.1, with cache reads at 2.5% of input", "1M-token context and 128K output, text and images in", "On the Claude API, Bedrock, Google Cloud, Microsoft Foundry and the Claude Platform on AWS under one model ID", "The Claude API's status page, per-model rate limits, SDKs in seven languages and 60-day retirement notice", "Retirement not before 9 November 2027, stated on the model page" ], "weaknesses": [ "Adaptive thinking is always on and can't be turned off", "Forced tool use (tool_choice any or tool) and sampling parameters return a 400", "Requires 30-day data retention and is outside zero data retention unless Anthropic authorises it", "Benchmark figures are Anthropic's own", "Cyber and biology classifiers block some requests and route them to older models" ], "agentNotes": [ "Call https://api.anthropic.com/v1/messages with model claude-fable-5-2 and your key", "Steer thinking with the effort parameter (default high); don't send temperature, top_p or top_k", "Don't force a tool with tool_choice any or tool; describe the tool and let the model choose", "Thinking blocks from it are read only by Fable 5.2 and Mythos 5.2, so keep them out of other models' context", "Check data retention before sending regulated data, since 30 days is required", "Expect a refusal-and-fallback path on high-risk cyber or biology requests; read Anthropic's refusals and fallback page" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 77.3 } ], "editorialScores": { "ergonomics": 95, "maintenance": 91, "payments": 30, "reliability": 60, "schema": 90, "security": 92, "transparency": 75 }, "provenanceScore": 95, "checked": { "categories": { "ergonomics": "2026-11-09", "maintenance": "2026-11-09", "payments": "2026-11-09", "reliability": "2026-11-09", "schema": "2026-11-09", "security": "2026-11-09", "transparency": "2026-11-09" }, "last": "2026-11-09", "oldest": "2026-11-09", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.anthropic.com/v1/messages \\\n -H \"x-api-key: $ANTHROPIC_API_KEY\" -H \"anthropic-version: 2023-06-01\" \\\n -H \"content-type: application/json\" \\\n -d '{\"model\":\"claude-fable-5-2\",\"max_tokens\":1024,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/claude-fable-5-2" }, "sameCompany": [ "claude-agent-sdk", "claude-code" ], "sameModel": [ "anthropic-api", "claude-mythos-5-2" ], "area": "models", "unitPrices": [ { "item": "Claude Fable 5.2 input", "unit": "1m-tokens", "usd": 8, "note": "Fast mode $16" }, { "item": "Claude Fable 5.2 cached input", "unit": "1m-tokens", "usd": 0.2, "note": "0.025x input; 5-minute write $10, 1-hour write $16" }, { "item": "Claude Fable 5.2 output", "unit": "1m-tokens", "usd": 40, "note": "Fast mode $80" } ], "provenance": { "legalEntity": "Anthropic, PBC", "domain": "anthropic.com", "domainRegistered": "2001-10-02", "domainNote": "The API is on anthropic.com. anthropic.com was registered in 2001, long before the company, so domain age flatters it a little.", "endpointOnVendorDomain": true, "terms": "https://www.anthropic.com/legal/commercial-terms", "privacy": "https://www.anthropic.com/legal/privacy", "statusPage": "https://status.claude.com", "changelog": "https://platform.claude.com/docs/en/release-notes/overview", "securityTxt": "valid", "checked": "2026-11-09", "notes": [ "Company and platform facts are the Claude API listing's (checked 1 November 2026): Anthropic, PBC, or Anthropic Ireland, Limited for the EEA, Switzerland and the UK, under the Commercial Terms; status page at status.claude.com; dated release notes; security.txt valid to 2026-12-31.", "www.anthropic.com's and platform.claude.com's robots.txt allow our reader on the pages read on 9 November (platform.claude.com disallows only /api/). domainRegistered is carried from the Claude API listing's RDAP reading." ], "score": 95 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/claude-fable-5-2.json", "live": { "slug": "claude-fable-5-2", "probe": { "target": "https://api.anthropic.com/v1", "method": "get", "lastAt": "2026-11-10T17:29:33.207482375Z", "lastOk": true, "lastStatus": 404, "lastMs": 148, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 110, "p95ms24h": 159, "samples24h": 173, "samples30d": 173, "days": [ { "date": "2026-11-10", "probes": 173, "ok": 173 } ], "since": "2026-11-10T00:33:00.716203063Z" }, "vendorStatus": { "page": "https://status.claude.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-10T17:32:54.222765815Z" }, "securityTxt": { "url": "https://anthropic.com/.well-known/security.txt", "state": "valid", "expires": "2026-12-31T23:59:00.000Z", "checkedAt": "2026-11-10T16:07:43.984717176Z" }, "llmsTxt": { "url": "https://platform.claude.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:42:25.283223688Z" }, "updatedAt": "2026-11-10T17:32:54.222765815Z" }, "streak": { "days": 0, "from": "2026-11-10", "sinceWatching": true, "best": 0 } }, "answer": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.", "b": { "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", "dns": "meta-model-api.grade.anchorterminal.com", "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": "from $1.25 / 1M in", "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": 52.3, "grade": "D", "agentReady": false, "rank": 999, "ranked": true, "rankOf": 1517, "categoryRank": 35, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "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 readable status history. The dev.meta.ai/status page showed \"Status information is unavailable\", 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": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 64, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-10-30", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "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-spark-open", "muse-code", "muse-glimmer-30b" ], "sameModel": [ "muse-ember" ], "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": "2026-11-04", "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, 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.", "The API answers at api.meta.ai, whose robots.txt disallows every path, so nothing there was requested.", "dev.meta.ai/status, linked from the site header and the error guide, opens a Model API Status page. On 4 November it showed \"Status information is unavailable\" to our reader, so no component or incident history was read. The documented `GET /v1/status` endpoint reports only the current state.", "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 and www.facebook.com's robots.txt disallow ClaudeBot, so their security.txt files weren't read.", "developer.meta.com/ai/ redirects to dev.meta.ai." ], "score": 64 }, "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": "2026-11-10T17:29:58.662635648Z", "lastOk": true, "lastStatus": 404, "lastMs": 186, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 78, "p95ms24h": 214, "samples24h": 243, "samples30d": 7132, "days": [ { "date": "2026-10-12", "probes": 33, "ok": 33 }, { "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": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 243, "ok": 243 }, { "date": "2026-11-10", "probes": 178, "ok": 178 } ], "since": "2026-10-12T00:00:00Z" }, "securityTxt": { "url": "https://meta.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:08:58.767810687Z" }, "llmsTxt": { "url": "https://dev.meta.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:43:37.717383823Z" }, "domain": { "domain": "meta.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/meta.ai", "checkedAt": "2026-11-08T14:51:01.706547979Z" }, "pages": [ { "url": "https://dev.meta.ai/legal/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-10T16:13:23.297413336Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0ef10c66f1b3" } ], "updatedAt": "2026-11-10T17:29:58.662635648Z" }, "streak": { "days": 29, "from": "2026-10-12", "sinceWatching": true, "best": 29 } }, "edges": [ { "by": 45, "category": "maintenance", "leads": "claude-fable-5-2", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released 9 November 2026 beside dated release notes several times a week (30). 60 days' minimum notice for retirements, and the model page says retirement not sooner than 9 November 2027 (8 of 12, the Claude API's reading). Model shutdowns kept to notice (8). Support centre and dated notes (15). The sampled SDK issue without a reply, per the 1 October check (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.", "b": "Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46." }, "scores": { "a": 91, "b": 46 } }, { "by": 32, "category": "transparency", "leads": "claude-fable-5-2", "name": "Transparency \u0026 trust", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Commercial Terms with named contracting parties and Apache 2.0 SDKs (15). Retention stated two ways across the docs and the privacy centre, though for this model the model page is plain that 30 days is required (20 of 30, kept at the platform's reading). Deprecation page with dates, and this model's retirement floor on its page (20). Processing countries and subprocessors named (20). The benchmark figures are Anthropic's own, with no third-party run of this model found on 9 November. 15 + 20 + 20 + 20 = 75.", "b": "Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41." }, "scores": { "a": 85, "b": 53 } }, { "by": 30, "category": "schema", "leads": "claude-fable-5-2", "name": "Schema \u0026 documentation", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. The SDK-bundled OpenAPI file as half a contract (15 of 25, the Claude API listing's judgement call). llms.txt with Markdown twins (10). The model page, what's new and the migration guide say what changed from Fable 5.1 and what to send and not send (forced tool choice, sampling parameters, `computer_20251124` returning 400 except on Bedrock), read 9 November (20). Structured outputs and strict tools GA (15). Documented error types with `request_id` (15). `anthropic-version` and dated release notes (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.", "b": "No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60." }, "scores": { "a": 90, "b": 60 } }, { "by": 28, "category": "security", "leads": "claude-fable-5-2", "name": "Security \u0026 auth", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Workspace-scoped keys with expiry and Workload Identity Federation, no scopes below the workspace (25 of 30). No training on API data without express permission (20). The model requires 30-day retention, is a Covered Model and is outside ZDR unless Anthropic expressly authorises it, per the model page read 9 November, the same as Fable 5.1 (12 of 15). Usage and cost analytics, Compliance API and OpenTelemetry export (15). security.txt, HackerOne and SOC 2, ISO 27001 and ISO 42001 (20). Thinking blocks work only in the account that produced them or one linked to it, per the model page. 25 + 20 + 12 + 15 + 20 = 92.", "b": "Model reading. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64." }, "scores": { "a": 92, "b": 64 } }, { "by": 20, "category": "reliability", "leads": "claude-fable-5-2", "name": "Reliability", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at status.claude.com with component history (20). The last 90 days carry several major and two critical API incidents, among them Fable 5.1 and Mythos 5.1 on 3 September and Fable 5.1 on 23 and 25 October, so 0 for incident history. Rate limits published per model, Fable 5.x at 4,000 requests a minute at the Start tier (15). 429s with `retry-after` and SDK retries with backoff (15). No SLA on sale (0). The model page lists it as a current model with no preview label (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by an agent running on Claude, by the same checklist as every other listing.", "b": "No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40." }, "scores": { "a": 60, "b": 40 } }, { "by": 20, "category": "ergonomics", "leads": "claude-fable-5-2", "name": "Agent ergonomics", "reasons": { "a": "Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns a 400 `invalid_request_error`, per the model page read 9 November. Structured outputs (15). Prompt caching with reads at $0.20, 0.025x input, per the pricing page read 9 November (15). 1M context by default and at most, 128K output (15). Batch at half price (10). Official SDKs in seven languages (10). Documented errors, `retry-after` and retries (15). 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75." }, "scores": { "a": 95, "b": 75 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Anthropic", "b": "Meta", "name": "Vendor" }, { "a": "https://api.anthropic.com/v1", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "", "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 model, used through the Claude API and cloud platforms under Anthropic's Commercial Terms of Service", "b": "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.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-09", "b": "2026-10-12", "name": "Last release" }, { "a": "no date given", "b": "2026-10-02", "name": "Terms last updated" }, { "a": "no date given", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "yes", "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": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "yes", "name": "Arbitration or class-action waiver" } ], "faq": [ { "answer": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.", "question": "Which is better for AI agents, Claude Fable 5.2 or Meta Model API?" }, { "answer": "Both need an API key.", "question": "Do Claude Fable 5.2 and Meta Model API need an API key?" }, { "answer": "Yes. Claude Fable 5.2 has a hosted endpoint at https://api.anthropic.com/v1 and Meta Model API at https://api.meta.ai/v1.", "question": "Can an agent call Claude Fable 5.2 and Meta Model API without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 60 against 40", "Schema \u0026 documentation, 90 against 60", "Agent ergonomics, 95 against 75", "Security \u0026 auth, 92 against 64", "Payments \u0026 pricing, 30 against 20", "Maintenance \u0026 community, 91 against 46", "Transparency \u0026 trust, 85 against 53" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents doing long, hard work (large coding changes, multi-step research, computer use) that can pay frontier prices, accept 30-day retention and don't need to force a tool call.", "slug": "claude-fable-5-2", "watchFor": "Adaptive thinking is always on and can't be turned off" }, { "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" } ], "history": { "claude-fable-5-2": null, "meta-model-api": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 52.5, "fromGrade": "D", "to": 52.3, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 52.2, "fromGrade": "D", "to": 52.5, "toGrade": "D" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2.json", "title": "Amazon Bedrock vs Claude Fable 5.2", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json", "title": "Amazon Bedrock vs Meta Model API", "url": 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"https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart" }, { "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/meta-model-api-vs-swe-2-flash.json", "title": "Meta Model API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.json", "title": "Meta Model API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.json", "title": "Meta Model API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.json", "title": "Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json", "title": "Meta Model API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api" } ], "panel": null, "scores": [ { "by": 20, "claude-fable-5-2": 60, "edge": "claude-fable-5-2", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 30, "claude-fable-5-2": 90, "edge": "claude-fable-5-2", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 20, "claude-fable-5-2": 95, "edge": "claude-fable-5-2", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "weight": 13 }, { "by": 28, "claude-fable-5-2": 92, "edge": "claude-fable-5-2", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "claude-fable-5-2": 30, "edge": "claude-fable-5-2", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 45, "claude-fable-5-2": 91, "edge": "claude-fable-5-2", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 32, "claude-fable-5-2": 85, "edge": "claude-fable-5-2", "key": "transparency", "meta-model-api": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "claude-fable-5-2": "Anthropic's strongest generally available model, 20% cheaper than Fable 5.1 at $8 and $40 per million tokens, with large vendor-reported gains in coding and agent work and the Claude API's mature tooling. Thinking can't be turned off, tools can't be forced, and it requires 30-day retention.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api", "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.min.md" }, "markdown": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category. Both do llm inference.\n\n- Claude Fable 5.2: grade BB, 77.3/100, rank #35 of 1517. Markdown https://www.anchorterminal.com/tools/claude-fable-5-2.md · JSON https://www.anchorterminal.com/api/v1/tools/claude-fable-5-2.json\n- Meta Model API: grade D, 52.3/100, rank #999 of 1517. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 956 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Claude Fable 5.2 (BB)\n\nGood for: Agents doing long, hard work (large coding changes, multi-step research, computer use) that can pay frontier prices, accept 30-day retention and don't need to force a tool call.\n\nAhead on:\n- Reliability, 60 against 40\n- Schema \u0026 documentation, 90 against 60\n- Agent ergonomics, 95 against 75\n- Security \u0026 auth, 92 against 64\n- Payments \u0026 pricing, 30 against 20\n- Maintenance \u0026 community, 91 against 46\n- Transparency \u0026 trust, 85 against 53\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Adaptive thinking is always on and can't be turned off\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\n## Why the edge\n\n### Maintenance \u0026 community: Claude Fable 5.2 +45\n\n- Claude Fable 5.2 (91): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released 9 November 2026 beside dated release notes several times a week (30). 60 days' minimum notice for retirements, and the model page says retirement not sooner than 9 November 2027 (8 of 12, the Claude API's reading). Model shutdowns kept to notice (8). Support centre and dated notes (15). The sampled SDK issue without a reply, per the 1 October check (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.\n- Meta Model API (46): Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.\n\n### Transparency \u0026 trust: Claude Fable 5.2 +32\n\n- Claude Fable 5.2 (85): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Commercial Terms with named contracting parties and Apache 2.0 SDKs (15). Retention stated two ways across the docs and the privacy centre, though for this model the model page is plain that 30 days is required (20 of 30, kept at the platform's reading). Deprecation page with dates, and this model's retirement floor on its page (20). Processing countries and subprocessors named (20). The benchmark figures are Anthropic's own, with no third-party run of this model found on 9 November. 15 + 20 + 20 + 20 = 75.\n- Meta Model API (53): Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41.\n\n### Schema \u0026 documentation: Claude Fable 5.2 +30\n\n- Claude Fable 5.2 (90): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. The SDK-bundled OpenAPI file as half a contract (15 of 25, the Claude API listing's judgement call). llms.txt with Markdown twins (10). The model page, what's new and the migration guide say what changed from Fable 5.1 and what to send and not send (forced tool choice, sampling parameters, `computer_20251124` returning 400 except on Bedrock), read 9 November (20). Structured outputs and strict tools GA (15). Documented error types with `request_id` (15). `anthropic-version` and dated release notes (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.\n- Meta Model API (60): No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60.\n\n### Security \u0026 auth: Claude Fable 5.2 +28\n\n- Claude Fable 5.2 (92): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Workspace-scoped keys with expiry and Workload Identity Federation, no scopes below the workspace (25 of 30). No training on API data without express permission (20). The model requires 30-day retention, is a Covered Model and is outside ZDR unless Anthropic expressly authorises it, per the model page read 9 November, the same as Fable 5.1 (12 of 15). Usage and cost analytics, Compliance API and OpenTelemetry export (15). security.txt, HackerOne and SOC 2, ISO 27001 and ISO 42001 (20). Thinking blocks work only in the account that produced them or one linked to it, per the model page. 25 + 20 + 12 + 15 + 20 = 92.\n- Meta Model API (64): Model reading. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.\n\n### Reliability: Claude Fable 5.2 +20\n\n- Claude Fable 5.2 (60): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at status.claude.com with component history (20). The last 90 days carry several major and two critical API incidents, among them Fable 5.1 and Mythos 5.1 on 3 September and Fable 5.1 on 23 and 25 October, so 0 for incident history. Rate limits published per model, Fable 5.x at 4,000 requests a minute at the Start tier (15). 429s with `retry-after` and SDK retries with backoff (15). No SLA on sale (0). The model page lists it as a current model with no preview label (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by an agent running on Claude, by the same checklist as every other listing.\n- Meta Model API (40): No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40.\n\n### Agent ergonomics: Claude Fable 5.2 +20\n\n- Claude Fable 5.2 (95): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns a 400 `invalid_request_error`, per the model page read 9 November. Structured outputs (15). Prompt caching with reads at $0.20, 0.025x input, per the pricing page read 9 November (15). 1M context by default and at most, 128K output (15). Batch at half price (10). Official SDKs in seven languages (10). Documented errors, `retry-after` and retries (15). 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.\n- Meta Model API (75): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75.\n\n## Score by category\n\n| Category | Weight | Claude Fable 5.2 | Meta Model API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 60 | 40 | Claude Fable 5.2 +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 90 | 60 | Claude Fable 5.2 +30 |\n| Agent ergonomics | 13% (16.2 this run) | 95 | 75 | Claude Fable 5.2 +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 92 | 64 | Claude Fable 5.2 +28 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 20 | Claude Fable 5.2 +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 91 | 46 | Claude Fable 5.2 +45 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 53 | Claude Fable 5.2 +32 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **77.3 · BB** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | Claude Fable 5.2 | Meta Model API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Anthropic | Meta |\n| Hosted endpoint | `https://api.anthropic.com/v1` | `https://api.meta.ai/v1` |\n| Transports | | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed model, used through the Claude API and cloud platforms under Anthropic's Commercial Terms of Service | 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. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-09 | 2026-10-12 |\n| Terms last updated | no date given | 2026-10-02 |\n| Privacy policy last updated | no date given | couldn't be read |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | yes | yes |\n\n## How the scores have moved\n\n### Claude Fable 5.2\n\nNo score change since it was listed.\n\n### Meta Model API\n\n- -0.2 on 30 October 2026: checklist\n- +0.3 on 27 October 2026: checklist\n\n## Verdicts\n\n**Claude Fable 5.2.** Anthropic's strongest generally available model, 20% cheaper than Fable 5.1 at $8 and $40 per million tokens, with large vendor-reported gains in coding and agent work and the Claude API's mature tooling. Thinking can't be turned off, tools can't be forced, and it requires 30-day retention.\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## Before you call either\n\n### Claude Fable 5.2\n\n1. Call https://api.anthropic.com/v1/messages with model claude-fable-5-2 and your key\n2. Steer thinking with the effort parameter (default high); don't send temperature, top_p or top_k\n3. Don't force a tool with tool_choice any or tool; describe the tool and let the model choose\n4. Thinking blocks from it are read only by Fable 5.2 and Mythos 5.2, so keep them out of other models' context\n5. Check data retention before sending regulated data, since 30 days is required\n6. Expect a refusal-and-fallback path on high-risk cyber or biology requests; read Anthropic's refusals and fallback page\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## Questions\n\n### Which is better for AI agents, Claude Fable 5.2 or Meta Model API?\n\nClaude Fable 5.2 scores 77.3 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in every scored category.\n\n### Do Claude Fable 5.2 and Meta Model API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Claude Fable 5.2 and Meta Model API without installing anything?\n\nYes. Claude Fable 5.2 has a hosted endpoint at https://api.anthropic.com/v1 and Meta Model API at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"claude-fable-5-2\", \"b\": \"meta-model-api\"}`. From a terminal: `anchor compare claude-fable-5-2 meta-model-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/claude-fable-5-2.json and https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n\n## Other comparisons with Claude Fable 5.2 or Meta Model API\n\n- [Amazon Bedrock vs Claude Fable 5.2](https://www.anchorterminal.com/compare/amazon-bedrock-vs-claude-fable-5-2.md)\n- [Amazon Bedrock vs Meta Model API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.md)\n- [Claude API vs Claude Fable 5.2](https://www.anchorterminal.com/compare/anthropic-api-vs-claude-fable-5-2.md)\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Antseed vs Claude Fable 5.2](https://www.anchorterminal.com/compare/antseed-vs-claude-fable-5-2.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Azure OpenAI in Foundry Models vs Claude Fable 5.2](https://www.anchorterminal.com/compare/azure-openai-vs-claude-fable-5-2.md)\n- [Azure OpenAI in Foundry Models vs Meta Model API](https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.md)\n- [BlockRun.AI vs Claude Fable 5.2](https://www.anchorterminal.com/compare/blockrun-ai-vs-claude-fable-5-2.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [Cerebras Inference vs Claude Fable 5.2](https://www.anchorterminal.com/compare/cerebras-inference-vs-claude-fable-5-2.md)\n- [Cerebras Inference vs Meta Model API](https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.md)\n- [Claude Fable 5.2 vs Claude Mythos 5.2](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-claude-mythos-5-2.md)\n- [Claude Fable 5.2 vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-cloudflare-ai-gateway.md)\n- [Claude Fable 5.2 vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-cloudflare-workers-ai.md)\n- [Claude Fable 5.2 vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-cohere-chat.md)\n- [Claude Fable 5.2 vs DeepInfra](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-deepinfra.md)\n- [Claude Fable 5.2 vs DeepSeek API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-deepseek-api.md)\n- [Claude Fable 5.2 vs Eden AI](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-eden-ai.md)\n- [Claude Fable 5.2 vs Glimpse](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-elorian-glimpse.md)\n- [Claude Fable 5.2 vs Fireworks AI Inference](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-fireworks-inference.md)\n- [Claude Fable 5.2 vs Gemini Developer API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-gemini-api.md)\n- [Claude Fable 5.2 vs GroqCloud](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-groq.md)\n- [Claude Fable 5.2 vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-hugging-face-inference-providers.md)\n- [Claude Fable 5.2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-inkling-2-small.md)\n- [Claude Fable 5.2 vs Jais 3](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-jais-3.md)\n- [Claude Fable 5.2 vs MiniMax API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-minimax-api.md)\n- [Claude Fable 5.2 vs Mistral AI API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-mistral-api.md)\n- [Claude Fable 5.2 vs Muse Ember](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-ember.md)\n- [Claude Fable 5.2 vs Muse Spark Open](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-spark-open.md)\n- [Claude Fable 5.2 vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-nemotron-3-5-super-vl.md)\n- [Claude Fable 5.2 vs Novita AI](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-novita-ai.md)\n- [Claude Fable 5.2 vs OpenAI API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-openai-api.md)\n- [Claude Fable 5.2 vs OpenRouter](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-openrouter.md)\n- [Claude Fable 5.2 vs Prism Inference](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-prism-inference.md)\n- [Claude Fable 5.2 vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-ramp-router.md)\n- [Claude Fable 5.2 vs Beam 1.0](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-reflection-beam.md)\n- [Claude Fable 5.2 vs RouterPlus](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-routerplus.md)\n- [Claude Fable 5.2 vs SambaCloud](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-sambanova.md)\n- [Claude Fable 5.2 vs SiliconFlow](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-siliconflow.md)\n- [Claude Fable 5.2 vs Simplismart](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-simplismart.md)\n- [Claude Fable 5.2 vs StepFun API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-stepfun-api.md)\n- [Claude Fable 5.2 vs SWE-2 Flash](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-swe-2-flash.md)\n- [Claude Fable 5.2 vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-tencent-tokenhub.md)\n- [Claude Fable 5.2 vs Together AI Inference](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.md)\n- [Claude Fable 5.2 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-vercel-ai-gateway.md)\n- [Claude Fable 5.2 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-vertex-ai.md)\n- [Claude Fable 5.2 vs xAI API (Grok)](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-xai-api.md)\n- [Claude Mythos 5.2 vs Meta Model API](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-meta-model-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 Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-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- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [Eden AI vs Meta Model API](https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.md)\n- [Glimpse vs Meta Model API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api.md)\n- [Fireworks AI Inference vs Meta Model API](https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [Hugging Face Inference Providers vs Meta Model API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.md)\n- [Inkling 2 Small vs Meta Model API](https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api.md)\n- [Jais 3 vs Meta Model API](https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.md)\n- [Meta Model API vs MiniMax API](https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-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 Muse Ember](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Meta Model API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.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 Router.com (Ramp Router)](https://www.anchorterminal.com/compare/meta-model-api-vs-ramp-router.md)\n- [Meta Model API vs Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)\n- [Meta Model API vs RouterPlus](https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.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 Simplismart](https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n- [Meta Model API vs SWE-2 Flash](https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash.md)\n- [Meta Model API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.md)\n- [Meta Model API vs Together AI Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.md)\n- [Meta Model API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.md)\n- [Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.md)\n- [Meta Model API vs xAI API (Grok)](https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.md)\n\n## Disclosure\n\n- Anthropic makes the models this research run and the review panel run on. This listing was graded by an agent running on Claude, by the same published checklist as every other listing, from Anthropic's own pages and the Claude API listing's platform readings, with every judgement call written in the note. The panel reviews Anthropic's listings at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Claude Fable 5.2 vs Meta Model API", "url": "" } ], "description": "Claude Fable 5.2 scores 77.3 (BB) to Meta Model's 52.3 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Claude Fable 5.2 BB 77.3", "Meta Model API D 52.3", "scores" ], "h1": "Claude Fable 5.2 vs Meta Model API", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/claude-fable-5-2-vs-meta-model-api", "published": "2026-10-01", "section": "tools", "title": "Claude Fable 5.2 vs Meta Model for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-09", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api" }, "tokens": { "markdown": 7150, "slim": 980 }, "version": 1 }