{ "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 Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on reliability.", "b": { "slug": "together-inference", "name": "Together AI Inference", "vendor": "Together Computer, Inc.", "vendorUrl": "https://www.together.ai", "kind": "http-api", "category": "inference", "summary": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput. Model-dependent capabilities include tool calling, structured outputs and vision.", "url": "https://www.anchorterminal.com/tools/together-inference", "markdownUrl": "https://www.anchorterminal.com/tools/together-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/together-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/together-inference.json", "dns": "together-inference.grade.anchorterminal.com", "repo": "https://github.com/togethercomputer/together-py", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.together.ai/v1", "packages": [ { "registry": "pypi", "name": "together", "main": true }, { "registry": "npm", "name": "together-ai", "main": true } ], "auth": "api-key", "authNotes": "Bearer API keys are scoped to projects, can expire and can be revoked separately. A key has full access to resources in its project. There are no per-key spending or rate limits; legacy default-project keys should be replaced.", "pricing": "paid", "pricingNotes": "Prepaid usage with a $15 minimum first credit purchase, then $5 minimum top-ups. No free trial. GPT OSS 120B is $0.15 per million input tokens and $0.60 per million output tokens. Dedicated hardware and provisioned throughput have separate rates.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 10, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://docs.together.ai", "llmsTxt": "https://docs.together.ai/llms.txt", "openapi": "https://docs.together.ai/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-23", "graded": true, "anchor": { "graded": true, "score": 67.8, "grade": "B", "agentReady": false, "rank": 304, "ranked": true, "rankOf": 1517, "categoryRank": 15, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 75, "schema": 93, "security": 70, "transparency": 74 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "2026-08-19 to 2026-08-27. Together removed GA serverless models with notice posted only on the day of removal. Changelog entries of 19, 21, 25 and 27 August say FLUX.1 schnell, Qwen2.5 7B, Kimi K2.6, Cogito v2.1 671B, Gemma 3n E4B, Llama Guard 4 12B, Nemotron 3 Ultra, Pearl's Gemma 4 31B, DeepSeek V4 Pro and Kimi K2.7 Code \"have been deprecated and are no longer available on serverless\", with no earlier entry announcing their removal and no preview label, while the deprecation policy promises 2 or 3 weeks' notice for serverless endpoints. Read at the floor, as fireworks-inference's same-day removals of 27 August were, -3 (https://docs.together.ai/docs/changelog.md)." ], "verdict": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.", "bestFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.", "strengths": [ "Public OpenAPI 3.1, Markdown documentation and Python and TypeScript SDKs", "Project-scoped API keys with optional expiry and per-key cost attribution", "Serverless, batch, dedicated and provisioned-throughput options", "Status page with a monitor per serverless model and 90 days of daily history", "US-only serverless processing through us-api.together.ai since 16 October 2026, at 1.25 times standard rates" ], "weaknesses": [ "A $15 credit purchase is required before platform access; no free trial", "Prompt and response storage is on by default; zero data retention must be enabled for the organisation", "Serverless has no guaranteed capacity outside provisioned throughput, and API keys have no individual spend caps", "Serverless models removed on 19, 21, 25 and 27 August 2026 were announced in the changelog only on the day" ], "agentNotes": [ "Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.", "For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.", "Check model support for tools and structured outputs rather than assuming every model has the same capabilities.", "Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.", "Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.", "Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.8 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 75, "schema": 93, "security": 70, "transparency": 65 }, "provenanceScore": 83, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.together.ai/v1/chat/completions' -H \"Authorization: Bearer $TOGETHER_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"openai/gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/together-inference" }, "sameCompany": [ "together-fine-tuning", "together-gpu-clusters", "together-code-sandbox" ], "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.15, "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.6, "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026" } ], "provenance": { "legalEntity": "Together Computer, Inc.", "domain": "together.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://www.together.ai/terms-of-service", "privacy": "https://www.together.ai/privacy", "statusPage": "https://status.together.ai", "changelog": "https://docs.together.ai/docs/changelog", "securityTxt": "valid", "checked": "2026-10-19", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "security.txt names the HackerOne programme and expires on 30 September 2028." ], "score": 83 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/together-inference.json", "live": { "slug": "together-inference", "probe": { "target": "https://api.together.ai/v1", "method": "get", "lastAt": "2026-11-10T17:30:25.240839332Z", "lastOk": true, "lastStatus": 404, "lastMs": 261, "authRequired": false, "uptime24h": 100, "uptime30d": 99.98, "p50ms24h": 210, "p95ms24h": 599, "samples24h": 243, "samples30d": 5506, "days": [ { "date": "2026-10-19", "probes": 173, "ok": 173 }, { "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": 250, "ok": 249 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "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": "2026-10-19T00:00:00Z" }, "vendorStatus": { "page": "https://status.together.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-03T15:50:27.832032204Z" }, "versions": [ { "registry": "github", "name": "togethercomputer/together-py", "version": "v3.1.1", "released": "2026-11-04", "seenAt": "2026-11-10T04:25:32.777071737Z" }, { "registry": "npm", "name": "together-ai", "version": "1.1.0", "seenAt": "2026-11-10T04:25:32.74826137Z" }, { "registry": "pypi", "name": "together", "version": "3.1.1", "released": "2026-11-04", "seenAt": "2026-11-10T04:25:32.631692985Z" } ], "githubStars": 12, "npmWeekly": 99070, "pypiWeekly": 432642, "securityTxt": { "url": "https://together.ai/.well-known/security.txt", "state": "valid", "expires": "2028-09-30T00:00:00.000Z", "checkedAt": "2026-11-10T16:08:07.811051873Z" }, "llmsTxt": { "url": "https://docs.together.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-10T15:44:59.235833106Z" }, "domain": { "domain": "together.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/together.ai", "checkedAt": "2026-11-08T14:49:59.126665901Z" }, "github": { "repo": "togethercomputer/together-py", "checkedAt": "2026-11-09T09:54:49.79539179Z", "stars": 12, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-08T04:08:32Z", "openIssues": 4, "openPRs": 45, "issuesOpened90d": 2, "issuesClosed90d": 1, "prsMerged90d": 96, "ci": { "branch": "main", "runs": 50, "success": 16, "failure": 0, "other": 34, "latest": "skipped", "latestAt": "2026-11-04T18:45:39Z" }, "replies": { "sampled": 7, "unanswered": 4, "medianDays": 14.2 } }, "updatedAt": "2026-11-10T17:30:25.240839332Z" }, "streak": { "days": 22, "from": "2026-10-19", "sinceWatching": true, "best": 22 } }, "edges": [ { "by": 26, "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": "Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0)." }, "scores": { "a": 91, "b": 65 } }, { "by": 22, "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": "Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20)." }, "scores": { "a": 92, "b": 70 } }, { "by": 15, "category": "reliability", "leads": "together-inference", "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": "Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75." }, "scores": { "a": 60, "b": 75 } }, { "by": 11, "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": "Proprietary service with published terms and Apache-2.0 SDK (15). Docs distinguish default content storage, training opt-in, organisation ZDR and passthrough models, but default content retention has no fixed duration in the reviewed pages (25 of 30). Public lifecycle policy gives a two-week migration window for breaking model upgrades and 2 or 3 weeks' notice for serverless removals, though removals on 19, 21, 25 and 27 August 2026 were posted only on the day (15 of 20). North American hosting and enterprise residency options are described; full subprocessor locations were not established (10 of 20)." }, "scores": { "a": 85, "b": 74 } }, { "by": 10, "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": "Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15)." }, "scores": { "a": 95, "b": 85 } }, { "by": 10, "category": "payments", "leads": "claude-fable-5-2", "name": "Payments \u0026 pricing", "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. No machine payment protocol on the pricing page, read 9 November (0). Per-token prices published without a login, $8 input and $40 output (20). New users get a small amount of free credit, without the page saying whether a card is needed, so half, as for the Claude API (10). Keys from the browser Console only (0). 0 + 20 + 10 + 0 = 30.", "b": "No machine payment protocol found in the reviewed billing and inference docs (0). Public token and capacity prices (20). No free trial and a $15 minimum first credit purchase (0). Browser account and payment setup required (0)." }, "scores": { "a": 30, "b": 20 } } ], "facts": [ { "a": "Model API", "b": "HTTP API", "name": "Kind" }, { "a": "Anthropic", "b": "Together Computer, Inc.", "name": "Vendor" }, { "a": "https://api.anthropic.com/v1", "b": "https://api.together.ai/v1", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Paid", "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": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-09", "b": "2026-10-23", "name": "Last release" }, { "a": "no date given", "b": "no date given", "name": "Terms last updated" }, { "a": "no date given", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "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": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "10 stars", "name": "Popularity" }, { "a": "none", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on reliability.", "question": "Which is better for AI agents, Claude Fable 5.2 or Together AI Inference?" }, { "answer": "Both need an API key.", "question": "Do Claude Fable 5.2 and Together AI Inference need an API key?" }, { "answer": "Yes. Claude Fable 5.2 has a hosted endpoint at https://api.anthropic.com/v1 and Together AI Inference at https://api.together.ai/v1.", "question": "Can an agent call Claude Fable 5.2 and Together AI Inference without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Agent ergonomics, 95 against 85", "Security \u0026 auth, 92 against 70", "Payments \u0026 pricing, 30 against 20", "Maintenance \u0026 community, 91 against 65", "Transparency \u0026 trust, 85 against 74" ], "also": [ "Agent-ready, a grade of BB or better", "No incidents deducted, where Together AI Inference loses 3 points for them" ], "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": [ "Reliability, 75 against 60" ], "also": null, "goodFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.", "slug": "together-inference", "watchFor": "A $15 credit purchase is required before platform access; no free trial" } ], "history": { "claude-fable-5-2": null, "together-inference": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-01", "delta": 0, "from": 67.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0, "from": 67.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" } ] }, "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-together-inference.json", 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"https://www.anchorterminal.com/compare/jais-3-vs-together-inference.json", "title": "Jais 3 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/jais-3-vs-together-inference" }, { "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/minimax-api-vs-together-inference.json", "title": "MiniMax API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-together-inference.json", "title": "Mistral AI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.json", "title": "Muse Ember vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.json", "title": "Muse Spark Open vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.json", "title": "Novita AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference.json", "title": "OpenAI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-together-inference.json", "title": "OpenRouter vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openrouter-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-together-inference.json", "title": "Prism Inference vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.json", "title": "Router.com (Ramp Router) vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.json", "title": "Beam 1.0 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-together-inference.json", "title": "RouterPlus vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/routerplus-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference.json", "title": "SambaCloud vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.json", "title": "SiliconFlow vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference.json", "title": "Simplismart vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.json", "title": "StepFun API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference.json", "title": "SWE-2 Flash vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.json", "title": "Tencent Cloud TokenHub vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.json", "title": "Together AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.json", "title": "Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api.json", "title": "Together AI Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference.json", "title": "Nemotron 3.5 Super VL vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference" } ], "panel": null, "scores": [ { "by": 15, "claude-fable-5-2": 60, "edge": "together-inference", "key": "reliability", "name": "Reliability", "together-inference": 75, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 3, "claude-fable-5-2": 90, "edge": "together-inference", "key": "schema", "name": "Schema \u0026 documentation", "together-inference": 93, "weight": 13 }, { "by": 10, "claude-fable-5-2": 95, "edge": "claude-fable-5-2", "key": "ergonomics", "name": "Agent ergonomics", "together-inference": 85, "weight": 13 }, { "by": 22, "claude-fable-5-2": 92, "edge": "claude-fable-5-2", "key": "security", "name": "Security \u0026 auth", "together-inference": 70, "weight": 14 }, { "by": 10, "claude-fable-5-2": 30, "edge": "claude-fable-5-2", "key": "payments", "name": "Payments \u0026 pricing", "together-inference": 20, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 26, "claude-fable-5-2": 91, "edge": "claude-fable-5-2", "key": "maintenance", "name": "Maintenance \u0026 community", "together-inference": 65, "weight": 7 }, { "by": 11, "claude-fable-5-2": 85, "edge": "claude-fable-5-2", "key": "transparency", "name": "Transparency \u0026 trust", "together-inference": 74, "weight": 7 } ], "summary": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on reliability. 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.", "together-inference": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference", "json": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.min.md" }, "markdown": "Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on reliability. 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- Together AI Inference: grade B, 67.8/100, rank #304 of 1517. Markdown https://www.anchorterminal.com/tools/together-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/together-inference.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- Agent ergonomics, 95 against 85\n- Security \u0026 auth, 92 against 70\n- Payments \u0026 pricing, 30 against 20\n- Maintenance \u0026 community, 91 against 65\n- Transparency \u0026 trust, 85 against 74\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No incidents deducted, where Together AI Inference loses 3 points for them\n\nWatch for: Adaptive thinking is always on and can't be turned off\n\n### Together AI Inference (B)\n\nGood for: Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.\n\nAhead on:\n- Reliability, 75 against 60\n\nWatch for: A $15 credit purchase is required before platform access; no free trial\n\n\n## Why the edge\n\n### Maintenance \u0026 community: Claude Fable 5.2 +26\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- Together AI Inference (65): Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0).\n\n### Security \u0026 auth: Claude Fable 5.2 +22\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- Together AI Inference (70): Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20).\n\n### Reliability: Together AI Inference +15\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- Together AI Inference (75): Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75.\n\n### Transparency \u0026 trust: Claude Fable 5.2 +11\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- Together AI Inference (74): Proprietary service with published terms and Apache-2.0 SDK (15). Docs distinguish default content storage, training opt-in, organisation ZDR and passthrough models, but default content retention has no fixed duration in the reviewed pages (25 of 30). Public lifecycle policy gives a two-week migration window for breaking model upgrades and 2 or 3 weeks' notice for serverless removals, though removals on 19, 21, 25 and 27 August 2026 were posted only on the day (15 of 20). North American hosting and enterprise residency options are described; full subprocessor locations were not established (10 of 20).\n\n### Agent ergonomics: Claude Fable 5.2 +10\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- Together AI Inference (85): Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15).\n\n### Payments \u0026 pricing: Claude Fable 5.2 +10\n\n- Claude Fable 5.2 (30): 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. No machine payment protocol on the pricing page, read 9 November (0). Per-token prices published without a login, $8 input and $40 output (20). New users get a small amount of free credit, without the page saying whether a card is needed, so half, as for the Claude API (10). Keys from the browser Console only (0). 0 + 20 + 10 + 0 = 30.\n- Together AI Inference (20): No machine payment protocol found in the reviewed billing and inference docs (0). Public token and capacity prices (20). No free trial and a $15 minimum first credit purchase (0). Browser account and payment setup required (0).\n\n## Score by category\n\n| Category | Weight | Claude Fable 5.2 | Together AI Inference | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 60 | 75 | Together AI Inference +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 90 | 93 | Together AI Inference +3 |\n| Agent ergonomics | 13% (16.2 this run) | 95 | 85 | Claude Fable 5.2 +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 92 | 70 | Claude Fable 5.2 +22 |\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 | 65 | Claude Fable 5.2 +26 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 74 | Claude Fable 5.2 +11 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **77.3 · BB** | **67.8 · B** | |\n\n## Facts side by side\n\n| Fact | Claude Fable 5.2 | Together AI Inference |\n| --- | --- | --- |\n| Kind | Model API | HTTP API |\n| Vendor | Anthropic | Together Computer, Inc. |\n| Hosted endpoint | `https://api.anthropic.com/v1` | `https://api.together.ai/v1` |\n| Transports | | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Paid |\n| x402 | no | no |\n| Licence | Closed model, used through the Claude API and cloud platforms under Anthropic's Commercial Terms of Service | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-09 | 2026-10-23 |\n| Terms last updated | no date given | no date given |\n| Privacy policy last updated | no date given | no date given |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | 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 | not found in the text |\n| Popularity | none | 10 stars |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Claude Fable 5.2\n\nNo score change since it was listed.\n\n### Together AI Inference\n\n- no change on 1 November 2026: new evidence, correction\n- no change 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**Together AI Inference.** A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.\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### Together AI Inference\n\n1. Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.\n2. For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.\n3. Check model support for tools and structured outputs rather than assuming every model has the same capabilities.\n4. Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.\n5. Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.\n6. Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths\n\n## Questions\n\n### Which is better for AI agents, Claude Fable 5.2 or Together AI Inference?\n\nClaude Fable 5.2 scores 77.3 (BB) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on reliability.\n\n### Do Claude Fable 5.2 and Together AI Inference need an API key?\n\nBoth need an API key.\n\n### Can an agent call Claude Fable 5.2 and Together AI Inference without installing anything?\n\nYes. Claude Fable 5.2 has a hosted endpoint at https://api.anthropic.com/v1 and Together AI Inference at https://api.together.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.json, and with the fewest tokens: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"claude-fable-5-2\", \"b\": \"together-inference\"}`. From a terminal: `anchor compare claude-fable-5-2 together-inference`\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/together-inference.json\n\n## Other comparisons with Claude Fable 5.2 or Together AI Inference\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 Together AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.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 Together AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.md)\n- [Antseed vs Claude Fable 5.2](https://www.anchorterminal.com/compare/antseed-vs-claude-fable-5-2.md)\n- [Antseed vs Together AI Inference](https://www.anchorterminal.com/compare/antseed-vs-together-inference.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 Together AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.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 Together AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-together-inference.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 Together AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference.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 Meta Model API](https://www.anchorterminal.com/compare/claude-fable-5-2-vs-meta-model-api.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 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 Together AI Inference](https://www.anchorterminal.com/compare/claude-mythos-5-2-vs-together-inference.md)\n- [Cloudflare AI Gateway vs Together AI Inference](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-together-inference.md)\n- [Cloudflare Workers AI vs Together AI Inference](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-together-inference.md)\n- [Cohere Chat API (Command models) vs Together AI Inference](https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference.md)\n- [DeepInfra vs Together AI Inference](https://www.anchorterminal.com/compare/deepinfra-vs-together-inference.md)\n- [DeepSeek API vs Together AI Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-together-inference.md)\n- [Eden AI vs Together AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.md)\n- [Glimpse vs Together AI Inference](https://www.anchorterminal.com/compare/elorian-glimpse-vs-together-inference.md)\n- [Fireworks AI Inference vs Together AI Inference](https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.md)\n- [Gemini Developer API vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-api-vs-together-inference.md)\n- [GroqCloud vs Together AI Inference](https://www.anchorterminal.com/compare/groq-vs-together-inference.md)\n- [Hugging Face Inference Providers vs Together AI Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.md)\n- [Inkling 2 Small vs Together AI Inference](https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference.md)\n- [Jais 3 vs Together AI Inference](https://www.anchorterminal.com/compare/jais-3-vs-together-inference.md)\n- [Meta Model API vs Together AI Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.md)\n- [MiniMax API vs Together AI Inference](https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.md)\n- [Mistral AI API vs Together AI Inference](https://www.anchorterminal.com/compare/mistral-api-vs-together-inference.md)\n- [Muse Ember vs Together AI Inference](https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.md)\n- [Muse Spark Open vs Together AI Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.md)\n- [Novita AI vs Together AI Inference](https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.md)\n- [OpenAI API vs Together AI Inference](https://www.anchorterminal.com/compare/openai-api-vs-together-inference.md)\n- [OpenRouter vs Together AI Inference](https://www.anchorterminal.com/compare/openrouter-vs-together-inference.md)\n- [Prism Inference vs Together AI Inference](https://www.anchorterminal.com/compare/prism-inference-vs-together-inference.md)\n- [Router.com (Ramp Router) vs Together AI Inference](https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.md)\n- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)\n- [RouterPlus vs Together AI Inference](https://www.anchorterminal.com/compare/routerplus-vs-together-inference.md)\n- [SambaCloud vs Together AI Inference](https://www.anchorterminal.com/compare/sambanova-vs-together-inference.md)\n- [SiliconFlow vs Together AI Inference](https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.md)\n- [Simplismart vs Together AI Inference](https://www.anchorterminal.com/compare/simplismart-vs-together-inference.md)\n- [StepFun API vs Together AI Inference](https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.md)\n- [SWE-2 Flash vs Together AI Inference](https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference.md)\n- [Tencent Cloud TokenHub vs Together AI Inference](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.md)\n- [Together AI Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.md)\n- [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md)\n- [Together AI Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/together-inference-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Together AI Inference](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference.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 Together AI Inference", "url": "" } ], "description": "Claude Fable 5.2 scores 77.3 (BB) to Together AI Inference's 67.8 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Claude Fable 5.2 BB 77.3", "Together AI Inference B 67.8", "scores" ], "h1": "Claude Fable 5.2 vs Together AI Inference", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/claude-fable-5-2-vs-together-inference", "published": "2026-10-01", "section": "tools", "title": "Claude Fable 5.2 vs Together AI Inference for AI agents (2026)", "toc": null, "updated": "2026-11-09", "url": "https://www.anchorterminal.com/compare/claude-fable-5-2-vs-together-inference" }, "tokens": { "markdown": 6700, "slim": 1030 }, "version": 1 }