{ "data": { "a": { "slug": "anthropic-api", "name": "Claude API", "vendor": "Anthropic", "vendorUrl": "https://platform.claude.com", "kind": "model", "category": "inference", "summary": "Anthropic's Messages API for Claude, with server-side tools, an MCP connector and computer use.", "url": "https://www.anchorterminal.com/tools/anthropic-api", "markdownUrl": "https://www.anchorterminal.com/tools/anthropic-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/anthropic-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/anthropic-api.json", "dns": "anthropic-api.grade.anchorterminal.com", "repo": "https://github.com/anthropics/anthropic-sdk-python", "license": "Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT)", "transports": [ "http" ], "remoteUrl": "https://api.anthropic.com/v1/messages", "packages": [ { "registry": "pypi", "name": "anthropic" }, { "registry": "npm", "name": "@anthropic-ai/sdk" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` header, with the legacy `x-api-key` header still accepted, plus `anthropic-version`. Personal and service-account keys are created in the Console for one workspace or several.", "pricing": "usage", "pricingNotes": "Prepaid credits. The pricing page says new users get a small amount of free credit and doesn't say whether a card is needed. Batch is half price. Cache writes cost 1.25x input for 5 minutes or 2x for an hour, reads 0.1x (0.05x on Opus 5.5 and Sonnet 5.5, 0.025x on Fable 5.1 and Mythos 5.1). Haiku 5.5 is priced by prompt length, $0.10/$0.50 per million up to 100,000 prompt tokens and $0.50/$2.50 above. US-only inference costs 1.1x. Fast mode on Opus 5.5 costs $8/$40 per million ($10/$50 on Opus 5 and 4.8, still in research preview; fast mode on Opus 4.8 is removed on 30 November 2026). Web search $10 per 1,000, web fetch billed as tokens only, code execution free alongside them or $0.05 per container hour after 1,550 free hours a month (https://platform.claude.com/docs/en/about-claude/pricing).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Access needs a Console account with a card on file.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 3900, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://platform.claude.com/docs", "rateLimitsUrl": "https://platform.claude.com/docs/en/api/rate-limits", "llmsTxt": "https://platform.claude.com/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "card-required", "llms-txt" ], "lastRelease": "2026-10-30", "graded": true, "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, 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": 34, "ranked": true, "rankOf": 1515, "categoryRank": 6, "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": "2026-11-01" }, "negative": 0, "verdict": "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.", "bestFor": "Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.", "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.", "strengths": [ "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model", "1M-token context on Opus 5.5, Sonnet 5.5 and Fable 5.1, with cache reads at $0.20 per million on Opus 5.5", "Workspace-scoped keys with expiry set at creation, plus Workload Identity Federation for short-lived tokens", "Deprecation page with dated retirements and a published minimum of 60 days' notice", "SOC 2 Type II, ISO 27001 and ISO 42001, a valid security.txt and a HackerOne programme" ], "weaknesses": [ "Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October", "Keys are created only in the browser Console, and there's no machine payment", "`tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5 and Fable 5.1, and thinking can't be disabled on Opus 5.5 or Fable 5.1", "Retention reads 'not retained by default' in the docs and 'deleted within 30 days' in the privacy centre", "No SLA on sale. Priority Tier's 99.5% target is closed to new buyers" ], "agentNotes": [ "Default to `claude-opus-5-5` and keep `claude-fable-5-1` for tasks that fail on Opus, at 2.5 times the price", "Don't send `tool_choice` any or tool to Opus 5.5, Sonnet 5.5 or Fable 5.1. Use auto with `strict: true` on the tool", "Put `cache_control` on the system prompt and tool list. Reads cost 0.05x input on Opus 5.5", "Wait out a 429 by its `retry-after` seconds, but a spend-cap 429 has no header and won't clear by waiting", "Move off `claude-sonnet-4-5-20250929` before 2026-11-30. Retired ids fail, they don't redirect", "Moving from `claude-haiku-4-5-20251001` to `claude-haiku-5-5`, drop temperature, top_p, top_k, prefill and `budget_tokens`, which return 400", "Pin your SDK major or `anthropic-version` deliberately. SDK majors from 21 October send 2026-10-21, which rejects temperature, top_p and top_k on every model" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "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": "2026-11-01", "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": "2026-10-08", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install anthropic # or: npm i @anthropic-ai/sdk", "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-opus-5-5\",\"max_tokens\":512,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/anthropic-api" }, "sameCompany": [ "claude-agent-sdk", "claude-code" ], "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 10 } ], "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": "2026-11-01", "score": 95 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "unknown", "freeTier": true, "minutes": 5, "credential": "api-key", "hosting": [ "US", "global" ], "euResidency": "no", "trainsOnData": "no", "zeroRetention": "enterprise", "certifications": [ "HIPAA (BAA available)" ], "selfHost": "no" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/anthropic-api.json", "live": { "slug": "anthropic-api", "probe": { "target": "https://api.anthropic.com/v1/messages", "method": "get", "lastAt": "2026-11-09T20:49:38.906049964Z", "lastOk": true, "lastStatus": 405, "lastMs": 38, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 29, "p95ms24h": 92, "samples24h": 244, "samples30d": 7881, "days": [ { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 212, "ok": 212 } ], "since": "2026-10-08T00:00:00Z" }, "vendorStatus": { "page": "https://status.claude.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-09T20:45:40.833153678Z" }, "versions": [ { "registry": "github", "name": "anthropics/anthropic-sdk-python", "version": "v2.6.0", "released": "2026-11-05", "seenAt": "2026-11-09T01:57:18.353211106Z" }, { "registry": "npm", "name": "@anthropic-ai/sdk", "version": "1.6.0", "seenAt": "2026-11-09T01:57:17.55747518Z" }, { "registry": "pypi", "name": "anthropic", "version": "2.6.0", "released": "2026-11-05", "seenAt": "2026-11-09T01:57:17.446019282Z" } ], "githubStars": 4059, "npmWeekly": 67619600, "pypiWeekly": 50413636, "securityTxt": { "url": "https://anthropic.com/.well-known/security.txt", "state": "valid", "expires": "2026-12-31T23:59:00.000Z", "checkedAt": "2026-11-09T16:05:18.439052351Z" }, "llmsTxt": { "url": "https://platform.claude.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-09T15:38:34.89490808Z" }, "domain": { "domain": "anthropic.com", "registered": "2001-10-02", "source": "https://rdap.verisign.com/com/v1/domain/anthropic.com", "checkedAt": "2026-11-08T15:01:02.784417293Z" }, "pages": [ { "url": "https://platform.claude.com/docs/en/about-claude/model-deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-09T15:47:37.770073575Z", "changedAt": "2026-11-04T08:29:53.452957567Z", "fingerprint": "5edba16fbe22" }, { "url": "https://platform.claude.com/docs/en/api/migration-2026-10-21", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-09T15:47:42.003475818Z", "changedAt": "2026-11-05T12:39:30.640753951Z", "fingerprint": "6ea9f16badc0" }, { "url": "https://platform.claude.com/docs/en/build-with-claude/fast-mode", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-09T15:47:44.073512118Z", "changedAt": "2026-11-04T08:29:59.946000043Z", "fingerprint": "52f70ae31e3b" }, { "url": "https://platform.claude.com/docs/en/release-notes/overview", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-09T15:47:46.046391549Z", "changedAt": "2026-11-07T14:16:45.429427327Z", "fingerprint": "4eeb5247777c" }, { "url": "https://platform.claude.com/docs/en/about-claude/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-09T15:47:39.961265387Z", "changedAt": "2026-11-06T13:38:18.52721709Z", "fingerprint": "0aed66e62ce0" }, { "url": "https://www.anthropic.com/legal/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-09T15:55:42.10648351Z", "changedAt": "2026-11-09T15:55:42.10648351Z", "fingerprint": "96d36a64a6d9" }, { "url": "https://www.anthropic.com/legal/commercial-terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-09T15:55:37.742072222Z", "changedAt": "2026-11-09T15:55:37.742072222Z", "fingerprint": "fe9d0cdde6ef" } ], "models": { "claude-fable-5-1": { "openrouterId": "anthropic/claude-fable-5.1", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-08T23:49:27.027409601Z" }, "claude-haiku-4-5-20251001": { "openrouterId": "anthropic/claude-haiku-4.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 200000, "maxOutput": 64000, "checkedAt": "2026-10-10T22:59:28.614012396Z" }, "claude-haiku-5-5": { "openrouterId": "anthropic/claude-haiku-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-08T23:49:27.027409601Z" }, "claude-opus-5-5": { "openrouterId": "anthropic/claude-opus-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-08T23:49:27.027409601Z" }, "claude-sonnet-5": { "openrouterId": "anthropic/claude-sonnet-5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-10-01T21:56:15.532848159Z" }, "claude-sonnet-5-5": { "openrouterId": "anthropic/claude-sonnet-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-08T23:49:27.027409601Z" } }, "github": { "repo": "anthropics/anthropic-sdk-python", "checkedAt": "2026-11-09T10:06:41.389228706Z", "stars": 4061, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-05T18:58:46Z", "openIssues": 71, "openPRs": 161, "issuesOpened90d": 63, "issuesClosed90d": 48, "prsMerged90d": 19, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-11-05T19:01:05Z" }, "advisories": [ { "ghsa": "GHSA-w828-4qhx-vxx3", "cve": "CVE-2026-34452", "severity": "medium", "published": "2026-03-31T17:53:42Z" }, { "ghsa": "GHSA-q5f5-3gjm-7mfm", "cve": "CVE-2026-34450", "severity": "medium", "published": "2026-03-31T17:53:28Z" } ], "replies": { "sampled": 25, "unanswered": 20, "medianDays": 15.1 } }, "updatedAt": "2026-11-09T20:49:38.906049964Z" }, "streak": { "days": 19, "from": "2026-10-21", "last": { "kind": "breaking", "date": "2026-10-21", "what": "API version 2026-10-21 released beside 2023-06-01. It rejects `temperature`, `top_p` and `top_k`, document blocks in assistant messages and citations in user messages with 400, and the new SDK majors (Python 2.0.0, TypeScript 1.0.0 and others) send it by default", "source": "https://platform.claude.com/docs/en/api/migration-2026-10-21" }, "next": { "kind": "shutdown", "date": "2026-11-30", "what": "`claude-sonnet-4-5-20250929` retires, replacement `claude-sonnet-5-5`", "source": "https://platform.claude.com/docs/en/about-claude/model-deprecations" }, "best": 19 } }, "answer": "Claude API scores 77.3 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in every scored category.", "b": { "slug": "muse-ember", "name": "Muse Ember", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Muse Ember is Meta's smallest and most efficient hosted model, built for sub-agent tasks, tool calls, routing and work over large collections of files and images, taking text, images, video, audio and PDF with a 1M-token context.", "url": "https://www.anchorterminal.com/tools/muse-ember", "markdownUrl": "https://www.anchorterminal.com/tools/muse-ember.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/muse-ember.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/muse-ember.json", "dns": "muse-ember.grade.anchorterminal.com", "license": "Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer", "transports": [], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer key from the API keys tab of the Model API dashboard, read from MODEL_API_KEY in Meta's examples, after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team and share its limits, with no scopes found, per the meta-model-api listing.", "pricing": "usage", "pricingNotes": "$0.10 per million input tokens, $0.004 cached and $0.50 output for requests up to 200K input tokens, and $0.30, $0.012 and $1.50 for the whole request above that. Standard mode only, no Contributor discount. Web search grounding $2.50 per 1,000 queries. Included in every Muse Code plan. No free API allowance found (checked 2026-11-09).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on Meta's pricing page, which bills tokens to a team account with a card (checked 2026-11-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-09" }, "docsUrl": "https://dev.meta.ai/docs/muse-ember", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "vision", "reasoning", "long-context", "tool-calling", "openai-compatible", "anthropic-compatible", "usage-priced", "card-required", "closed-source", "llms-txt", "new" ], "lastRelease": "2026-11-09", "graded": true, "anchor": { "graded": true, "score": 51.8, "grade": "D", "agentReady": false, "rank": 1017, "ranked": true, "rankOf": 1515, "categoryRank": 36, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-09" }, "negative": 0, "verdict": "A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights.", "bestFor": "Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.", "strengths": [ "$0.10 input, $0.004 cached and $0.50 output per million tokens up to 200K input, published without a login", "Text, image, video, audio and PDF in, a 1,048,576-token context and up to 524,288 output tokens", "The same request body as Muse Spark and Muse Wonder on Responses, Chat Completions and Messages endpoints", "Tool calling, structured output, computer use and search grounding", "Reasoning effort from minimal to max, with clear guidance on what to hand it and what not to", "3,000 requests and 4,000,000 tokens a minute per team, published" ], "weaknesses": [ "No weights and no parameter count published, so it can't be run locally", "Requests over 200K input tokens are billed at three times the rate for the whole request", "Default reasoning effort is max, which spends output tokens on simple routing calls unless set lower", "No readable status page, SLA, deprecation policy or API changelog, per the meta-model-api listing", "Benchmark and cost figures are Meta's own, several on internal benchmarks" ], "agentNotes": [ "Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY", "Set the effort explicitly, reasoning.effort on Responses or reasoning_effort on Chat Completions. It defaults to max, and none isn't accepted; minimal or low suits classification and routing", "Keep input under 200K tokens a request, cached tokens and previous_response_id history included, or the whole request bills at the long-context rate", "Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises", "Use strict structured output for extraction and routing steps", "In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide" ], "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": 51.8 } ], "editorialScores": { "ergonomics": 72, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 64, "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 -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"muse-ember-1.0\",\n \"input\": \"Classify this support ticket as billing, bug, or feature request.\",\n \"reasoning\": {\"effort\": \"low\"}\n}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/muse-ember" }, "sameCompany": [ "muse-spark-open", "muse-code", "muse-glimmer-30b" ], "sameModel": [ "meta-model-api" ], "area": "models", "unitPrices": [ { "item": "Muse Ember input", "unit": "1m-tokens", "usd": 0.1, "note": "Up to 200K input tokens a request; $0.30 above, for the whole request" }, { "item": "Muse Ember cached input", "unit": "1m-tokens", "usd": 0.004, "note": "$0.012 above 200K input tokens" }, { "item": "Muse Ember output", "unit": "1m-tokens", "usd": 0.5, "note": "$1.50 above 200K input tokens" } ], "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": "2026-11-09", "notes": [ "Company and platform facts are the meta-model-api listing's (checked 4 November 2026): Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, under the 9 October 2026 terms; no readable status page; no Model API changelog; no security.txt on dev.meta.ai.", "dev.meta.ai's and research.meta.ai's robots.txt allow our reader on the pages read on 9 November. domainRegistered is carried from the meta-model-api listing's RDAP reading." ], "score": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/muse-ember.json", "live": { "slug": "muse-ember", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-11-09T20:50:02.257490788Z", "lastOk": true, "lastStatus": 404, "lastMs": 46, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 48, "p95ms24h": 72, "samples24h": 10, "samples30d": 10, "days": [ { "date": "2026-11-09", "probes": 10, "ok": 10 } ], "since": "2026-11-09T19:55:51.172718582Z" }, "updatedAt": "2026-11-09T20:50:02.257490788Z" }, "streak": { "days": 0, "from": "2026-11-09", "sinceWatching": true, "best": 0 } }, "edges": [ { "by": 45, "category": "maintenance", "leads": "anthropic-api", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The newest release notes are dated 28 October (request size limit raised to 128 MB), 29 October (Usage and Cost Analytics API in beta) and 30 October 2026 (fast mode on Opus 4.8 deprecated, removal on 30 November) (30). Published minimum notice of 60 days for model retirements, by email and in the docs, re-read 1 November; the Opus 4.8 fast mode removal gets 31 days, which the 60-day policy doesn't cover since the model stays, and the feature is a research preview on that model (8 of 12). One model shutdown date in the last 90 days, Opus 4.1 on 5 August, kept to its notice (8 of 8). Dated release notes several times a week and a support centre (15 of 15). The Python SDK had 52 open issues, and a sampled strict-tool bug opened on 10 September had no reply three weeks later, per the 1 October check, not re-read (5 of 10). Current official SDKs, Python `anthropic` 2.3.0 and TypeScript `sdk-v1.3.0`, both tagged 23 October, after new major versions (Python 2.0.0, TypeScript 1.0.0) on 21 October that send API version 2026-10-21 by default (15). Supported runtimes stated, Python 3.10 to 3.14 (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.", "b": "Model reading. Released 9 November 2026 (30). No deprecation policy or notice period found, per the platform reading (0 of 12). Dated launches on the API, the latest Muse Wonder on 12 October and Muse Ember on 9 November (8 of 8). No Model API changelog; a help centre with tickets (8 of 15). No SDK of Meta's own (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46." }, "scores": { "a": 91, "b": 46 } }, { "by": 32, "category": "transparency", "leads": "anthropic-api", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service with clear commercial terms (effective 17 June 2025, re-read 1 November, with Anthropic Ireland, Limited as the contracting party for customers in the EEA, Switzerland and the UK and Anthropic, PBC elsewhere, per the 15 October check). The SDKs moved from MIT to Apache 2.0 with the major versions of 21 October, both OSI licences (15). The privacy policy is effective 10 September 2026, re-read 1 November. Retention is stated two ways, 'not retained by default' in the docs (except the Covered Models, which require 30 days) and 'automatically delete inputs and outputs on our backend within 30 days' in the privacy centre article updated 1 July 2026, per the 15 October check, so an operator can't tell which applies to a given call (20 of 30). Deprecation page with announcement and retirement dates (20). Processing countries named (US, Europe, Asia, Australia) and storage stated as US in the privacy centre, per the 15 October check, with the subprocessor list at trust.anthropic.com per the 1 October check (20). 15 + 20 + 20 + 20 = 75.", "b": "Editorial half. Closed model under the Model API terms, with clear terms and law; no weights and no parameter count, unlike Muse Spark Open and Muse Glimmer (15). Standard content isn't used for training, retention periods not stated outside zero retention (18 of 30). No deprecation policy or dated notices (0). A subprocessor list linked but not read, no data locations (8 of 20). 15 + 18 + 0 + 8 = 41." }, "scores": { "a": 85, "b": 53 } }, { "by": 30, "category": "schema", "leads": "anthropic-api", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI document in the docs. The Python SDK repository bundles a Stainless-generated OpenAPI 3.1 file (`scripts/mock-spec.json.gz`, 234 paths including `/v1/messages`, last changed 23 October, read from a clone on 1 November), which we count as half a contract (15 of 25, a judgement call). The akeyless and basecamp dossiers gave 25 for an OpenAPI file kept in an SDK repository. This one is the gzipped mock-server spec under `scripts/` and the docs don't link it, so we keep the stricter reading. llms.txt indexes 845 pages, each with a Markdown twin, re-read 1 November (10). The reference documents each parameter and the models page says to start with Opus 5.5 for most workloads (20). Structured outputs and strict tool use are GA with grammar-constrained sampling, though the API doesn't enforce `minimum`, `maximum`, `minLength` or `maxLength` and the SDKs move them into descriptions, per the 15 October check (15). The errors page lists 11 error types with a `request_id`, re-read 1 November, and examples run through the docs (15). `anthropic-version` header, with a second version, 2026-10-21, released on 21 October beside 2023-06-01 and documented with a migration guide, and dated release notes with an RSS feed, newest 30 October (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.", "b": "Model reading. No OpenAPI file; the Markdown reference is the contract, per the meta-model-api listing (0). llms.txt and Markdown copies of every page (10). The Muse Ember page and choose-a-model page say what to hand it and what not to (hard single-shot coding, knowledge-heavy questions, visual coding), with model ID, inputs, context, max output and effort range (18 of 20). JSON Schema tools and output, reasoning effort an enum, per the platform reading (12 of 15). Curl, Python and TypeScript examples and the platform's error guide (15). A versioned model ID and a dated launch post, with no API changelog (5 of 15). 0 + 10 + 18 + 12 + 15 + 5 = 60." }, "scores": { "a": 90, "b": 60 } }, { "by": 28, "category": "security", "leads": "anthropic-api", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Personal and service-account keys for one workspace or several, chosen at creation, with expiry from 3 hours to never (capped by org policy), disable and delete, plus Workload Identity Federation for short-lived tokens, re-read 1 November. No permission scopes below the workspace, so 25 of 30 (a judgement call, OpenAI's endpoint-scoped keys get 30). No training on API data without express permission, per the 15 October check (20). Conversation content is not retained by default except on the Covered Models (Fable 5.1, Mythos 5.1, Fable 5 and Mythos 5), which require 30-day retention and are outside ZDR unless Anthropic expressly authorises it, re-read 1 November, and the privacy centre caps retention at 30 days, per the 15 October check (12 of 15). Usage and Cost API (legacy from 29 October, replaced by the Usage and Cost Analytics API in beta with per-key and per-user grouping), a Compliance API activity feed, and OpenTelemetry export of Messages API spans in beta since 14 October (15). security.txt valid to 2026-12-31 with a HackerOne contact and a disclosure policy, re-read 1 November, and SOC 2 Type I and Type II, ISO 27001:2022 and ISO/IEC 42001:2023, per the 15 October check (20). 25 + 20 + 12 + 15 + 20 = 92.", "b": "Platform readings are the meta-model-api listing's of 4 November. Team keys, named, revocable, no scopes (20 of 30). Standard mode only, so content isn't used to train Meta models under the terms, with safety use reserved (17 of 20). Retention 'as needed' with zero retention through sales (10 of 15). Usage dashboard by model, no per-call log (5 of 15). No security.txt on dev.meta.ai, a bug bounty and a security commitments page, no named certification (12 of 20). 20 + 17 + 10 + 5 + 12 = 64." }, "scores": { "a": 92, "b": 64 } }, { "by": 23, "category": "ergonomics", "leads": "anthropic-api", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5, Fable 5.1 and Mythos 5.1, re-read 1 November, so a tool can't be forced on the larger current models. Structured outputs GA (15). Prompt caching with reads at 0.1x input, 0.05x on Opus 5.5 and Sonnet 5.5 and 0.025x on Fable 5.1 and Mythos 5.1 (15). 1M context on the default model (15). Batch at half price (10). Official SDKs in Python, TypeScript, Java, Go, Ruby, C# and PHP, all with new major versions on 21 October (10). Documented error types, `retry-after` and SDK retries with backoff (15). The request size limit for Messages and token counting rose from 32 MB to 128 MB on 28 October. 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.", "b": "Model reading. Tool calls, parallel calls, computer use and search grounding, with tool_choice limited to auto per the platform reading (15 of 20). Strict structured output (15). Automatic prompt caching, cached input at 4% of the input price (15). A 1,048,576-token context, but requests over 200K input tokens bill at three times the rate for the whole request (12 of 15). No batch endpoint (0). No SDK of Meta's own; OpenAI and Anthropic SDKs against compatible endpoints (0). OpenAI-style errors with fixes and retryable codes (15). 15 + 15 + 15 + 12 + 0 + 0 + 15 = 72." }, "scores": { "a": 95, "b": 72 } }, { "by": 20, "category": "reliability", "leads": "anthropic-api", "name": "Reliability", "reasons": { "a": "Status page at status.claude.com with component history (20). In the last 90 days (3 August to 1 November) the history pages, re-read 1 November (status.claude.com's robots.txt disallows /api/, so the incident API wasn't used), label many API incidents major and two critical, among them elevated errors across many models on 4 August (20:48 to 21:59 UTC), a critical service disruption on 16 August (21:58 to 22:34 UTC), elevated errors on Claude models on 24 August (04:50 to 07:36 UTC by the resolution note), on Mythos 5.1, Fable 5.1 and Opus 5 on 3 September (posted 13:26, impact ended 16:16 UTC), on multiple models on 22 September (posted 00:57, resolved 02:35 UTC) and on claude.ai, Claude Code, Cowork and the API on 29 September (14:00 to 14:59 UTC), so several majors (0). Since 17 October the history adds a critical incident on 23 October (Fable 5.1, Sonnet 5.5, Haiku 5.5 and fast mode on Opus 5.5, 23:28 to 23:59 UTC), and majors on Opus 5.5 on 24 October (00:31 to 00:37 UTC), Fable 5 and 5.1 on 24 October (05:16 to 05:53 UTC), Sonnet 5.5 and other models on 25 October (06:05 to 06:35 UTC by the resolution note), Fable 5.1 on 25 October (08:17 to 08:49 UTC) and Sonnet 5.5 twice on 27 October (09:14 to 09:56 and 15:09 to 15:50 UTC). The 21 and 29 July incidents left the window. Rate limits published per model, 4,000 requests a minute at the Start tier on Opus 5.5, Sonnet 5.5, Haiku 5.5 and Fable 5.x and 1,000 on older models, re-read 1 November (15). 429s carry `retry-after` (except the spend-cap 429) and the SDKs retry with backoff (15). No SLA on sale. Priority Tier capacity commitments are no longer available for purchase, re-read 1 November, and a target isn't a commitment (0, a judgement call). Messages API is GA (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by agents running on Claude, by the same checklist as every other listing.", "b": "Model reading, for the surface it's called on, Meta Model API. No status page with readable history, per the meta-model-api listing's 4 November check (0), so no readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-ember-1.0, read 9 November (15). 429 and 503 with Retry-After, backoff guidance and rate-limit headers, per the meta-model-api listing (15). No SLA found (0). Muse Ember carries no preview label, but the API opened as a public preview in July and no general-availability notice was found, so half, as for the platform (5). 0 + 5 + 15 + 15 + 0 + 5 = 40." }, "scores": { "a": 60, "b": 40 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Anthropic", "b": "Meta", "name": "Vendor" }, { "a": "https://api.anthropic.com/v1/messages", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "", "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": "Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT)", "b": "Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-11-09", "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" }, { "a": "3.9k stars", "b": "none", "name": "Popularity" }, { "a": "3.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Claude API scores 77.3 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in every scored category.", "question": "Which is better for AI agents, Claude API or Muse Ember?" }, { "answer": "Both need an API key.", "question": "Do Claude API and Muse Ember need an API key?" }, { "answer": "Yes. Claude API has a hosted endpoint at https://api.anthropic.com/v1/messages and Muse Ember at https://api.meta.ai/v1.", "question": "Can an agent call Claude API and Muse Ember without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 60 against 40", "Schema \u0026 documentation, 90 against 60", "Agent ergonomics, 95 against 72", "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": "Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.", "slug": "anthropic-api", "watchFor": "Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October" }, { "aheadOn": null, "also": null, "goodFor": "Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.", "slug": "muse-ember", "watchFor": "No weights and no parameter count published, so it can't be run locally" } ], "history": { "anthropic-api": [ { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.3, "from": 77.6, "fromGrade": "BB", "to": 77.3, "toGrade": "BB" } ], "muse-ember": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.json", "title": "Amazon Bedrock vs Claude API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.json", "title": "Amazon Bedrock vs Muse Ember", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-antseed.json", "title": "Claude API vs Antseed", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-antseed" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.json", "title": "Claude API vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.json", "title": "Claude API vs BlockRun.AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.json", "title": "Claude API vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway.json", "title": "Claude API vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai.json", "title": "Claude API vs Cloudflare Workers AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.json", "title": "Claude API vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra.json", "title": "Claude API vs DeepInfra", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.json", "title": "Claude API vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.json", "title": "Claude API vs Eden AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse.json", "title": "Claude API vs Glimpse", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.json", "title": "Claude API vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.json", "title": "Claude API vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq.json", "title": "Claude API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.json", "title": "Claude API vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.json", "title": "Claude API vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.json", "title": "Claude API vs Jais 3", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json", "title": "Claude API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.json", "title": "Claude API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.json", "title": "Claude API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.json", "title": "Claude API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl.json", "title": "Claude API vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.json", "title": "Claude API vs Novita AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.json", "title": "Claude API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter.json", "title": "Claude API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.json", "title": "Claude API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router.json", "title": "Claude API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.json", "title": "Claude API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus.json", "title": "Claude API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.json", "title": "Claude API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.json", "title": "Claude API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart.json", "title": "Claude API vs Simplismart", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api.json", "title": "Claude API vs StepFun API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash.json", "title": "Claude API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.json", "title": "Claude API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.json", "title": "Claude API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.json", "title": "Claude API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.json", "title": "Claude API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.json", "title": "Claude API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-muse-ember.json", "title": "Antseed vs Muse Ember", "url": "https://www.anchorterminal.com/compare/antseed-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-ember.json", "title": "Azure OpenAI in Foundry Models vs Muse Ember", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-ember.json", "title": "BlockRun.AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-ember.json", "title": "Cerebras Inference vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-ember.json", "title": "Cloudflare AI Gateway vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-ember.json", "title": "Cloudflare Workers AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember.json", "title": "Cohere Chat API (Command models) vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-ember.json", "title": "DeepInfra vs Muse Ember", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember.json", "title": "DeepSeek API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-ember.json", "title": "Eden AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.json", "title": "Glimpse vs Muse Ember", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-ember.json", "title": "Fireworks AI Inference vs Muse Ember", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-ember.json", "title": "Gemini Developer API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-muse-ember.json", "title": "GroqCloud vs Muse Ember", "url": "https://www.anchorterminal.com/compare/groq-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-ember.json", "title": "Hugging Face Inference Providers vs Muse Ember", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.json", "title": "Inkling 2 Small vs Muse Ember", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-muse-ember.json", "title": "Jais 3 vs Muse Ember", "url": "https://www.anchorterminal.com/compare/jais-3-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember.json", "title": "Meta Model API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-ember.json", "title": "MiniMax API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-ember.json", "title": "Mistral AI API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open.json", "title": "Muse Ember vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-nemotron-3-5-super-vl.json", "title": "Muse Ember vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai.json", "title": "Muse Ember vs Novita AI", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api.json", "title": "Muse Ember vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-openrouter.json", "title": "Muse Ember vs OpenRouter", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-prism-inference.json", "title": "Muse Ember vs Prism Inference", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-ramp-router.json", "title": "Muse Ember vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.json", "title": "Muse Ember vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-routerplus.json", "title": "Muse Ember vs RouterPlus", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.json", "title": "Muse Ember vs SambaCloud", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow.json", "title": "Muse Ember vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-simplismart.json", "title": "Muse Ember vs Simplismart", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api.json", "title": "Muse Ember vs StepFun API", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash.json", "title": "Muse Ember vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub.json", "title": "Muse Ember vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub" }, { "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-ember-vs-vercel-ai-gateway.json", "title": "Muse Ember vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai.json", "title": "Muse Ember vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.json", "title": "Muse Ember vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-xai-api" } ], "panel": null, "scores": [ { "anthropic-api": 60, "by": 20, "edge": "anthropic-api", "key": "reliability", "muse-ember": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "anthropic-api": 90, "by": 30, "edge": "anthropic-api", "key": "schema", "muse-ember": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "anthropic-api": 95, "by": 23, "edge": "anthropic-api", "key": "ergonomics", "muse-ember": 72, "name": "Agent ergonomics", "weight": 13 }, { "anthropic-api": 92, "by": 28, "edge": "anthropic-api", "key": "security", "muse-ember": 64, "name": "Security \u0026 auth", "weight": 14 }, { "anthropic-api": 30, "by": 10, "edge": "anthropic-api", "key": "payments", "muse-ember": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "anthropic-api": 91, "by": 45, "edge": "anthropic-api", "key": "maintenance", "muse-ember": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "anthropic-api": 85, "by": 32, "edge": "anthropic-api", "key": "transparency", "muse-ember": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Claude API scores 77.3 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in every scored category. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "anthropic-api": "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.", "muse-ember": "A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember", "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.min.md" }, "markdown": "Claude API scores 77.3 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in every scored category. Both do llm inference.\n\n- Claude API: grade BB, 77.3/100, rank #34 of 1515. Markdown https://www.anchorterminal.com/tools/anthropic-api.md · JSON https://www.anchorterminal.com/api/v1/tools/anthropic-api.json\n- Muse Ember: grade D, 51.8/100, rank #1017 of 1515. Markdown https://www.anchorterminal.com/tools/muse-ember.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-ember.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 871 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Claude API (BB)\n\nGood for: Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.\n\nAhead on:\n- Reliability, 60 against 40\n- Schema \u0026 documentation, 90 against 60\n- Agent ergonomics, 95 against 72\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: Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October\n\n### Muse Ember (D)\n\nGood for: Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.\n\nWatch for: No weights and no parameter count published, so it can't be run locally\n\n\n## Why the edge\n\n### Maintenance \u0026 community: Claude API +45\n\n- Claude API (91): Model reading. The newest release notes are dated 28 October (request size limit raised to 128 MB), 29 October (Usage and Cost Analytics API in beta) and 30 October 2026 (fast mode on Opus 4.8 deprecated, removal on 30 November) (30). Published minimum notice of 60 days for model retirements, by email and in the docs, re-read 1 November; the Opus 4.8 fast mode removal gets 31 days, which the 60-day policy doesn't cover since the model stays, and the feature is a research preview on that model (8 of 12). One model shutdown date in the last 90 days, Opus 4.1 on 5 August, kept to its notice (8 of 8). Dated release notes several times a week and a support centre (15 of 15). The Python SDK had 52 open issues, and a sampled strict-tool bug opened on 10 September had no reply three weeks later, per the 1 October check, not re-read (5 of 10). Current official SDKs, Python `anthropic` 2.3.0 and TypeScript `sdk-v1.3.0`, both tagged 23 October, after new major versions (Python 2.0.0, TypeScript 1.0.0) on 21 October that send API version 2026-10-21 by default (15). Supported runtimes stated, Python 3.10 to 3.14 (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.\n- Muse Ember (46): Model reading. Released 9 November 2026 (30). No deprecation policy or notice period found, per the platform reading (0 of 12). Dated launches on the API, the latest Muse Wonder on 12 October and Muse Ember on 9 November (8 of 8). No Model API changelog; a help centre with tickets (8 of 15). No SDK of Meta's own (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.\n\n### Transparency \u0026 trust: Claude API +32\n\n- Claude API (85): Closed service with clear commercial terms (effective 17 June 2025, re-read 1 November, with Anthropic Ireland, Limited as the contracting party for customers in the EEA, Switzerland and the UK and Anthropic, PBC elsewhere, per the 15 October check). The SDKs moved from MIT to Apache 2.0 with the major versions of 21 October, both OSI licences (15). The privacy policy is effective 10 September 2026, re-read 1 November. Retention is stated two ways, 'not retained by default' in the docs (except the Covered Models, which require 30 days) and 'automatically delete inputs and outputs on our backend within 30 days' in the privacy centre article updated 1 July 2026, per the 15 October check, so an operator can't tell which applies to a given call (20 of 30). Deprecation page with announcement and retirement dates (20). Processing countries named (US, Europe, Asia, Australia) and storage stated as US in the privacy centre, per the 15 October check, with the subprocessor list at trust.anthropic.com per the 1 October check (20). 15 + 20 + 20 + 20 = 75.\n- Muse Ember (53): Editorial half. Closed model under the Model API terms, with clear terms and law; no weights and no parameter count, unlike Muse Spark Open and Muse Glimmer (15). Standard content isn't used for training, retention periods not stated outside zero retention (18 of 30). No deprecation policy or dated notices (0). A subprocessor list linked but not read, no data locations (8 of 20). 15 + 18 + 0 + 8 = 41.\n\n### Schema \u0026 documentation: Claude API +30\n\n- Claude API (90): No OpenAPI document in the docs. The Python SDK repository bundles a Stainless-generated OpenAPI 3.1 file (`scripts/mock-spec.json.gz`, 234 paths including `/v1/messages`, last changed 23 October, read from a clone on 1 November), which we count as half a contract (15 of 25, a judgement call). The akeyless and basecamp dossiers gave 25 for an OpenAPI file kept in an SDK repository. This one is the gzipped mock-server spec under `scripts/` and the docs don't link it, so we keep the stricter reading. llms.txt indexes 845 pages, each with a Markdown twin, re-read 1 November (10). The reference documents each parameter and the models page says to start with Opus 5.5 for most workloads (20). Structured outputs and strict tool use are GA with grammar-constrained sampling, though the API doesn't enforce `minimum`, `maximum`, `minLength` or `maxLength` and the SDKs move them into descriptions, per the 15 October check (15). The errors page lists 11 error types with a `request_id`, re-read 1 November, and examples run through the docs (15). `anthropic-version` header, with a second version, 2026-10-21, released on 21 October beside 2023-06-01 and documented with a migration guide, and dated release notes with an RSS feed, newest 30 October (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.\n- Muse Ember (60): Model reading. No OpenAPI file; the Markdown reference is the contract, per the meta-model-api listing (0). llms.txt and Markdown copies of every page (10). The Muse Ember page and choose-a-model page say what to hand it and what not to (hard single-shot coding, knowledge-heavy questions, visual coding), with model ID, inputs, context, max output and effort range (18 of 20). JSON Schema tools and output, reasoning effort an enum, per the platform reading (12 of 15). Curl, Python and TypeScript examples and the platform's error guide (15). A versioned model ID and a dated launch post, with no API changelog (5 of 15). 0 + 10 + 18 + 12 + 15 + 5 = 60.\n\n### Security \u0026 auth: Claude API +28\n\n- Claude API (92): Model reading. Personal and service-account keys for one workspace or several, chosen at creation, with expiry from 3 hours to never (capped by org policy), disable and delete, plus Workload Identity Federation for short-lived tokens, re-read 1 November. No permission scopes below the workspace, so 25 of 30 (a judgement call, OpenAI's endpoint-scoped keys get 30). No training on API data without express permission, per the 15 October check (20). Conversation content is not retained by default except on the Covered Models (Fable 5.1, Mythos 5.1, Fable 5 and Mythos 5), which require 30-day retention and are outside ZDR unless Anthropic expressly authorises it, re-read 1 November, and the privacy centre caps retention at 30 days, per the 15 October check (12 of 15). Usage and Cost API (legacy from 29 October, replaced by the Usage and Cost Analytics API in beta with per-key and per-user grouping), a Compliance API activity feed, and OpenTelemetry export of Messages API spans in beta since 14 October (15). security.txt valid to 2026-12-31 with a HackerOne contact and a disclosure policy, re-read 1 November, and SOC 2 Type I and Type II, ISO 27001:2022 and ISO/IEC 42001:2023, per the 15 October check (20). 25 + 20 + 12 + 15 + 20 = 92.\n- Muse Ember (64): Platform readings are the meta-model-api listing's of 4 November. Team keys, named, revocable, no scopes (20 of 30). Standard mode only, so content isn't used to train Meta models under the terms, with safety use reserved (17 of 20). Retention 'as needed' with zero retention through sales (10 of 15). Usage dashboard by model, no per-call log (5 of 15). No security.txt on dev.meta.ai, a bug bounty and a security commitments page, no named certification (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.\n\n### Agent ergonomics: Claude API +23\n\n- Claude API (95): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5, Fable 5.1 and Mythos 5.1, re-read 1 November, so a tool can't be forced on the larger current models. Structured outputs GA (15). Prompt caching with reads at 0.1x input, 0.05x on Opus 5.5 and Sonnet 5.5 and 0.025x on Fable 5.1 and Mythos 5.1 (15). 1M context on the default model (15). Batch at half price (10). Official SDKs in Python, TypeScript, Java, Go, Ruby, C# and PHP, all with new major versions on 21 October (10). Documented error types, `retry-after` and SDK retries with backoff (15). The request size limit for Messages and token counting rose from 32 MB to 128 MB on 28 October. 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.\n- Muse Ember (72): Model reading. Tool calls, parallel calls, computer use and search grounding, with tool_choice limited to auto per the platform reading (15 of 20). Strict structured output (15). Automatic prompt caching, cached input at 4% of the input price (15). A 1,048,576-token context, but requests over 200K input tokens bill at three times the rate for the whole request (12 of 15). No batch endpoint (0). No SDK of Meta's own; OpenAI and Anthropic SDKs against compatible endpoints (0). OpenAI-style errors with fixes and retryable codes (15). 15 + 15 + 15 + 12 + 0 + 0 + 15 = 72.\n\n### Reliability: Claude API +20\n\n- Claude API (60): Status page at status.claude.com with component history (20). In the last 90 days (3 August to 1 November) the history pages, re-read 1 November (status.claude.com's robots.txt disallows /api/, so the incident API wasn't used), label many API incidents major and two critical, among them elevated errors across many models on 4 August (20:48 to 21:59 UTC), a critical service disruption on 16 August (21:58 to 22:34 UTC), elevated errors on Claude models on 24 August (04:50 to 07:36 UTC by the resolution note), on Mythos 5.1, Fable 5.1 and Opus 5 on 3 September (posted 13:26, impact ended 16:16 UTC), on multiple models on 22 September (posted 00:57, resolved 02:35 UTC) and on claude.ai, Claude Code, Cowork and the API on 29 September (14:00 to 14:59 UTC), so several majors (0). Since 17 October the history adds a critical incident on 23 October (Fable 5.1, Sonnet 5.5, Haiku 5.5 and fast mode on Opus 5.5, 23:28 to 23:59 UTC), and majors on Opus 5.5 on 24 October (00:31 to 00:37 UTC), Fable 5 and 5.1 on 24 October (05:16 to 05:53 UTC), Sonnet 5.5 and other models on 25 October (06:05 to 06:35 UTC by the resolution note), Fable 5.1 on 25 October (08:17 to 08:49 UTC) and Sonnet 5.5 twice on 27 October (09:14 to 09:56 and 15:09 to 15:50 UTC). The 21 and 29 July incidents left the window. Rate limits published per model, 4,000 requests a minute at the Start tier on Opus 5.5, Sonnet 5.5, Haiku 5.5 and Fable 5.x and 1,000 on older models, re-read 1 November (15). 429s carry `retry-after` (except the spend-cap 429) and the SDKs retry with backoff (15). No SLA on sale. Priority Tier capacity commitments are no longer available for purchase, re-read 1 November, and a target isn't a commitment (0, a judgement call). Messages API is GA (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by agents running on Claude, by the same checklist as every other listing.\n- Muse Ember (40): Model reading, for the surface it's called on, Meta Model API. No status page with readable history, per the meta-model-api listing's 4 November check (0), so no readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-ember-1.0, read 9 November (15). 429 and 503 with Retry-After, backoff guidance and rate-limit headers, per the meta-model-api listing (15). No SLA found (0). Muse Ember carries no preview label, but the API opened as a public preview in July and no general-availability notice was found, so half, as for the platform (5). 0 + 5 + 15 + 15 + 0 + 5 = 40.\n\n## Score by category\n\n| Category | Weight | Claude API | Muse Ember | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 60 | 40 | Claude API +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 90 | 60 | Claude API +30 |\n| Agent ergonomics | 13% (16.2 this run) | 95 | 72 | Claude API +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 92 | 64 | Claude API +28 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 20 | Claude API +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 API +45 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 53 | Claude API +32 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **77.3 · BB** | **51.8 · D** | |\n\n## Facts side by side\n\n| Fact | Claude API | Muse Ember |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Anthropic | Meta |\n| Hosted endpoint | `https://api.anthropic.com/v1/messages` | `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 | Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT) | Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-11-09 |\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| Popularity | 3.9k stars | none |\n| Agent reviews | 3.5/5 (4) | none |\n\n## How the scores have moved\n\n### Claude API\n\n- -0.3 on 8 October 2026: checklist\n\n### Muse Ember\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Claude API.** Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.\n\n**Muse Ember.** A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights.\n\n## Before you call either\n\n### Claude API\n\n1. Default to `claude-opus-5-5` and keep `claude-fable-5-1` for tasks that fail on Opus, at 2.5 times the price\n2. Don't send `tool_choice` any or tool to Opus 5.5, Sonnet 5.5 or Fable 5.1. Use auto with `strict: true` on the tool\n3. Put `cache_control` on the system prompt and tool list. Reads cost 0.05x input on Opus 5.5\n4. Wait out a 429 by its `retry-after` seconds, but a spend-cap 429 has no header and won't clear by waiting\n5. Move off `claude-sonnet-4-5-20250929` before 2026-11-30. Retired ids fail, they don't redirect\n6. Moving from `claude-haiku-4-5-20251001` to `claude-haiku-5-5`, drop temperature, top_p, top_k, prefill and `budget_tokens`, which return 400\n7. Pin your SDK major or `anthropic-version` deliberately. SDK majors from 21 October send 2026-10-21, which rejects temperature, top_p and top_k on every model\n\n### Muse Ember\n\n1. Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY\n2. Set the effort explicitly, reasoning.effort on Responses or reasoning_effort on Chat Completions. It defaults to max, and none isn't accepted; minimal or low suits classification and routing\n3. Keep input under 200K tokens a request, cached tokens and previous_response_id history included, or the whole request bills at the long-context rate\n4. Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises\n5. Use strict structured output for extraction and routing steps\n6. In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide\n\n## Questions\n\n### Which is better for AI agents, Claude API or Muse Ember?\n\nClaude API scores 77.3 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in every scored category.\n\n### Do Claude API and Muse Ember need an API key?\n\nBoth need an API key.\n\n### Can an agent call Claude API and Muse Ember without installing anything?\n\nYes. Claude API has a hosted endpoint at https://api.anthropic.com/v1/messages and Muse Ember at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.json, and with the fewest tokens: https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"anthropic-api\", \"b\": \"muse-ember\"}`. From a terminal: `anchor compare anthropic-api muse-ember`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/anthropic-api.json and https://www.anchorterminal.com/api/v1/tools/muse-ember.json\n\n## Other comparisons with Claude API or Muse Ember\n\n- [Amazon Bedrock vs Claude API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.md)\n- [Amazon Bedrock vs Muse Ember](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.md)\n- [Claude API vs Antseed](https://www.anchorterminal.com/compare/anthropic-api-vs-antseed.md)\n- [Claude API vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.md)\n- [Claude API vs BlockRun.AI](https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.md)\n- [Claude API vs Cerebras Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.md)\n- [Claude API vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway.md)\n- [Claude API vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai.md)\n- [Claude API vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.md)\n- [Claude API vs DeepInfra](https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra.md)\n- [Claude API vs DeepSeek API](https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.md)\n- [Claude API vs Eden AI](https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md)\n- [Claude API vs Glimpse](https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse.md)\n- [Claude API vs Fireworks AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.md)\n- [Claude API vs Gemini Developer API](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.md)\n- [Claude API vs GroqCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-groq.md)\n- [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md)\n- [Claude API vs Inkling 2 Small](https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.md)\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Claude API vs MiniMax API](https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.md)\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Claude API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl.md)\n- [Claude API vs Novita AI](https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.md)\n- [Claude API vs OpenAI API](https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.md)\n- [Claude API vs OpenRouter](https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter.md)\n- [Claude API vs Prism Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.md)\n- [Claude API vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router.md)\n- [Claude API vs Beam 1.0](https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.md)\n- [Claude API vs RouterPlus](https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Claude API vs SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Claude API vs Simplismart](https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart.md)\n- [Claude API vs StepFun API](https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api.md)\n- [Claude API vs SWE-2 Flash](https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash.md)\n- [Claude API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.md)\n- [Claude API vs Together AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.md)\n- [Claude API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.md)\n- [Claude API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.md)\n- [Claude API vs xAI API (Grok)](https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.md)\n- [Antseed vs Muse Ember](https://www.anchorterminal.com/compare/antseed-vs-muse-ember.md)\n- [Azure OpenAI in Foundry Models vs Muse Ember](https://www.anchorterminal.com/compare/azure-openai-vs-muse-ember.md)\n- [BlockRun.AI vs Muse Ember](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-ember.md)\n- [Cerebras Inference vs Muse Ember](https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-ember.md)\n- [Cloudflare AI Gateway vs Muse Ember](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-ember.md)\n- [Cloudflare Workers AI vs Muse Ember](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-ember.md)\n- [Cohere Chat API (Command models) vs Muse Ember](https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember.md)\n- [DeepInfra vs Muse Ember](https://www.anchorterminal.com/compare/deepinfra-vs-muse-ember.md)\n- [DeepSeek API vs Muse Ember](https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember.md)\n- [Eden AI vs Muse Ember](https://www.anchorterminal.com/compare/eden-ai-vs-muse-ember.md)\n- [Glimpse vs Muse Ember](https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.md)\n- [Fireworks AI Inference vs Muse Ember](https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-ember.md)\n- [Gemini Developer API vs Muse Ember](https://www.anchorterminal.com/compare/gemini-api-vs-muse-ember.md)\n- [GroqCloud vs Muse Ember](https://www.anchorterminal.com/compare/groq-vs-muse-ember.md)\n- [Hugging Face Inference Providers vs Muse Ember](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-ember.md)\n- [Inkling 2 Small vs Muse Ember](https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.md)\n- [Jais 3 vs Muse Ember](https://www.anchorterminal.com/compare/jais-3-vs-muse-ember.md)\n- [Meta Model API vs Muse Ember](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember.md)\n- [MiniMax API vs Muse Ember](https://www.anchorterminal.com/compare/minimax-api-vs-muse-ember.md)\n- [Mistral AI API vs Muse Ember](https://www.anchorterminal.com/compare/mistral-api-vs-muse-ember.md)\n- [Muse Ember vs Muse Spark Open](https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open.md)\n- [Muse Ember vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/muse-ember-vs-nemotron-3-5-super-vl.md)\n- [Muse Ember vs Novita AI](https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai.md)\n- [Muse Ember vs OpenAI API](https://www.anchorterminal.com/compare/muse-ember-vs-openai-api.md)\n- [Muse Ember vs OpenRouter](https://www.anchorterminal.com/compare/muse-ember-vs-openrouter.md)\n- [Muse Ember vs Prism Inference](https://www.anchorterminal.com/compare/muse-ember-vs-prism-inference.md)\n- [Muse Ember vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/muse-ember-vs-ramp-router.md)\n- [Muse Ember vs Beam 1.0](https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.md)\n- [Muse Ember vs RouterPlus](https://www.anchorterminal.com/compare/muse-ember-vs-routerplus.md)\n- [Muse Ember vs SambaCloud](https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.md)\n- [Muse Ember vs SiliconFlow](https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow.md)\n- [Muse Ember vs Simplismart](https://www.anchorterminal.com/compare/muse-ember-vs-simplismart.md)\n- [Muse Ember vs StepFun API](https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api.md)\n- [Muse Ember vs SWE-2 Flash](https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash.md)\n- [Muse Ember vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub.md)\n- [Muse Ember vs Together AI Inference](https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.md)\n- [Muse Ember vs Vercel AI Gateway](https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway.md)\n- [Muse Ember vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai.md)\n- [Muse Ember vs xAI API (Grok)](https://www.anchorterminal.com/compare/muse-ember-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 agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, 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": "2026-11-09", "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 API vs Muse Ember", "url": "" } ], "description": "Claude scores 77.3 (BB) to Muse Ember's 51.8 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Claude API BB 77.3", "Muse Ember D 51.8", "scores" ], "h1": "Claude API vs Muse Ember", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/anthropic-api-vs-muse-ember", "published": "2026-10-01", "section": "tools", "title": "Claude vs Muse Ember for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-09", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember" }, "tokens": { "markdown": 7000, "slim": 930 }, "version": 1 }