{ "data": { "a": { "slug": "meta-model-api", "name": "Meta Model API", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Meta Model API is Meta's pay-as-you-go API for its hosted Muse models, including Muse Wonder and Muse Spark, through OpenAI-style Responses and Chat Completions endpoints and an Anthropic-style Messages endpoint, plus image, speech and segmentation routes.", "url": "https://www.anchorterminal.com/tools/meta-model-api", "markdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/meta-model-api.json", "dns": "meta-model-api.grade.anchorterminal.com", "license": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "transports": [ "http" ], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer API key created on the API keys tab of the Model API dashboard after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team, are shown once and are revoked by deletion. No key scopes were found, and every key on a team shares the team's rate limits.", "pricing": "usage", "pricingNotes": "Muse Wonder is $4.00 per million input tokens, $0.20 cached and $20.00 per million output tokens, Standard mode only (checked 2026-10-12). Muse Spark is $1.25, $0.15 and $4.25, or $0.10, $0.002 and $0.20 in Contributor mode, where Meta may train on the content. Billed in arrears to a card. No free allowance was found.", "priceSummary": "from $1.25 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in dev.meta.ai/llms.txt, the pricing page, the API reference or the billing help pages, checked 12 October 2026. Usage is charged to a card at a payment threshold or on the 1st of each month.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-12" }, "docsUrl": "https://dev.meta.ai/docs/overview", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "image.generate", "image.edit", "speech.stt", "speech.streaming" ], "tags": [ "official", "hosted", "model", "usage-priced", "closed-source", "llms-txt", "multimodal", "streaming", "openai-compatible", "anthropic-compatible", "card-required" ], "lastRelease": "2026-10-12", "graded": true, "anchor": { "graded": true, "score": 52.3, "grade": "D", "agentReady": false, "rank": 989, "ranked": true, "rankOf": 1486, "categoryRank": 33, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "bestFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "strengths": [ "Muse Wonder and Muse Spark take text, image, video, audio and PDF input with a 1,048,576-token context window", "Per-token prices, per-model rate limits and rate-limit headers published without a login", "Content sent in Standard mode is not used to train Meta models, and training use is opt-in through `-contributor` model IDs", "Responses, Chat Completions and Messages endpoints, so the OpenAI and Anthropic SDKs work with a base-URL change", "llms.txt and a Markdown copy of every docs page, with an error guide that gives the Retry-After value for each retryable error" ], "weaknesses": [ "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found", "No free API allowance found, and billing is set up with a card", "No readable status history. The dev.meta.ai/status page showed \"Status information is unavailable\", and `/v1/status` reports only the current state", "`tool_choice` accepts only `auto`, so a call can't be forced or ruled out", "No OpenAPI file, batch endpoint or Model API changelog found, and API keys have no scopes" ], "agentNotes": [ "Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests", "Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content", "Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key", "Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`", "Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "ergonomics": 75, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 64, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-10-30", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"muse-spark-1.3\", \"input\": \"What is the capital of France?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/meta-model-api" }, "sameCompany": [ "muse-spark-open", "muse-code", "muse-glimmer-30b" ], "area": "models", "unitPrices": [ { "item": "Muse Wonder input", "unit": "1m-tokens", "usd": 4, "note": "Standard mode, muse-wonder-1.0. No long-context premium." }, { "item": "Muse Wonder cached input", "unit": "1m-tokens", "usd": 0.2 }, { "item": "Muse Wonder output", "unit": "1m-tokens", "usd": 20 }, { "item": "Muse Spark input", "unit": "1m-tokens", "usd": 1.25, "note": "Standard mode, muse-spark-1.3, 1.2 and 1.1." }, { "item": "Muse Spark cached input", "unit": "1m-tokens", "usd": 0.15 }, { "item": "Muse Spark output", "unit": "1m-tokens", "usd": 4.25 }, { "item": "Muse Spark input, Contributor mode", "unit": "1m-tokens", "usd": 0.1, "note": "Meta may use the content to train its models." }, { "item": "Muse Spark output, Contributor mode", "unit": "1m-tokens", "usd": 0.2, "note": "Cached input is $0.002 per million tokens." }, { "item": "Web search grounding", "unit": "1k-requests", "usd": 2.5, "note": "Per 1,000 search queries, on top of token cost." }, { "item": "Muse Image generated image", "unit": "image", "usd": 0.01 } ], "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://dev.meta.ai/legal/terms-of-service", "privacy": "https://www.facebook.com/privacy/policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The terms (last updated 9 October 2026) are an agreement with Meta Platforms, Inc., or Meta Platforms Ireland Limited for users in the European Region. The model card names the same two.", "The privacy field is the Meta Privacy Policy, which the terms link. www.facebook.com's robots.txt asks readers like ours not to fetch it, so it wasn't read. The terms also link a subprocessor list at forwork.meta.com/legal/mfw-subprocessor-list/ and the Meta Global Processor Terms, neither of which was read.", "The API answers at api.meta.ai, whose robots.txt disallows every path, so nothing there was requested.", "dev.meta.ai/status, linked from the site header and the error guide, opens a Model API Status page. On 4 November it showed \"Status information is unavailable\" to our reader, so no component or incident history was read. The documented `GET /v1/status` endpoint reports only the current state.", "No Model API changelog was found. The only changelog on dev.meta.ai is Muse Code's.", "dev.meta.ai/.well-known/security.txt returns 404. www.meta.ai's and www.facebook.com's robots.txt disallow ClaudeBot, so their security.txt files weren't read.", "developer.meta.com/ai/ redirects to dev.meta.ai." ], "score": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/meta-model-api.json", "live": { "slug": "meta-model-api", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-11-07T18:20:39.224681736Z", "lastOk": true, "lastStatus": 404, "lastMs": 168, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 73, "p95ms24h": 200, "samples24h": 239, "samples30d": 6412, "days": [ { "date": "2026-10-12", "probes": 33, "ok": 33 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "securityTxt": { "url": "https://meta.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:02:03.890144289Z" }, "llmsTxt": { "url": "https://dev.meta.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:07.335168045Z" }, "domain": { "domain": "meta.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/meta.ai", "checkedAt": "2026-11-01T14:15:25.518716318Z" }, "pages": [ { "url": "https://dev.meta.ai/legal/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:02:46.050794947Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0ef10c66f1b3" } ], "updatedAt": "2026-11-07T18:20:39.224681736Z" } }, "answer": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in 6 of 7 scored categories.", "b": { "slug": "xai-api", "name": "xAI API (Grok)", "vendor": "SpaceXSI (xAI)", "vendorUrl": "https://x.ai", "kind": "model", "category": "inference", "summary": "xAI's API for its Grok models (the docs now name the company SpaceXSI), with text, image, video and voice endpoints, server-side search and remote MCP tools, through an OpenAI-compatible REST API or gRPC.", "url": "https://www.anchorterminal.com/tools/xai-api", "markdownUrl": "https://www.anchorterminal.com/tools/xai-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/xai-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/xai-api.json", "dns": "xai-api.grade.anchorterminal.com", "repo": "https://github.com/xai-org/xai-sdk-python", "license": "Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://api.x.ai/v1", "packages": [ { "registry": "pypi", "name": "xai-sdk" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a team API key from console.x.ai. Keys can be limited to endpoints and models by ACL, capped by QPM and TPM, given an expiry, and rotated or disabled through the Management API. mTLS is documented as an option, and GitHub secret scanning disables leaked keys.", "pricing": "usage", "pricingNotes": "Prepaid credits, then the default payment method at month end. Grok 4.7 costs $2 input, $0.50 cached input and $6 output per 1M tokens below 200K prompt tokens, and $4/$1/$12 above, applied to the whole request. Batch is 20% off on grok-4.7, 4.6, 4.5, 4.3 and the grok-4.20 models. Priority processing 2x, the US regional endpoint 1.1x. Web search, code execution and attachment search $5 per 1,000 calls, collections search $2.50, X search $5 per 1,000 posts. $0.05 fee for a request blocked before generation for a usage-policy violation (https://docs.x.ai/developers/pricing, checked 2026-11-06).", "priceSummary": "from $1.25 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, llms.txt or the OpenAPI spec. Access needs a console account loaded with prepaid credits (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 597, "npmWeekly": null, "pypiWeekly": 912149, "asOf": "2026-11-06" }, "docsUrl": "https://docs.x.ai", "rateLimitsUrl": "https://docs.x.ai/developers/rate-limits", "llmsTxt": "https://docs.x.ai/llms.txt", "openapi": "https://docs.x.ai/openapi.json", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "prepaid", "openapi", "llms-txt", "openai-compatible", "closed-source", "python", "batch", "status-page", "bug-bounty", "soc2" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 71.7, "grade": "BB", "agentReady": true, "rank": 151, "ranked": true, "rankOf": 1486, "categoryRank": 8, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 90, "maintenance": 77, "payments": 20, "reliability": 55, "schema": 88, "security": 97, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.", "bestFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.", "strengths": [ "Grok 4.7 at $2/$6 per million tokens below 200K prompt tokens, with a 500K context and 20% off through the Batch API", "API keys restricted by endpoint and model ACLs, with QPM and TPM caps, expiry and a rotate endpoint", "Self-serve team-wide zero data retention, confirmed on every response by an `x-zero-data-retention` header", "OpenAPI 3.1 spec, llms.txt and a Markdown twin of every docs page", "security.txt valid to 2027-06-29 and a HackerOne bug bounty" ], "weaknesses": [ "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August", "No SLA, no free tier for the text API, and no Retry-After header documented for 429s", "No stated minimum notice for retirements, and retired slugs are served by a different model at its price", "Remote MCP doesn't support `require_approval`, so server-side tool calls run without an approval step", "The terms, privacy policy and DPA at x.ai/legal answered a Cloudflare block on 6 October and 6 November 2026, so they weren't read" ], "agentNotes": [ "Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated", "Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price", "Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2", "Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context", "Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6" ], "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": 71.7 } ], "editorialScores": { "ergonomics": 90, "maintenance": 77, "payments": 20, "reliability": 55, "schema": 88, "security": 97, "transparency": 52 }, "provenanceScore": 73, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install xai-sdk # or: pip install openai, with base_url https://api.x.ai/v1", "http": "curl https://api.x.ai/v1/responses \\\n -H \"Authorization: Bearer $XAI_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"grok-4.7\",\"input\":\"What is the meaning of life?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/xai-api" }, "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 5 }, { "item": "Code execution tool", "unit": "1k-requests", "usd": 5 }, { "item": "Collections search tool", "unit": "1k-requests", "usd": 2.5 } ], "provenance": { "legalEntity": "", "domain": "x.ai", "domainRegistered": "2017-12-16", "domainNote": "x.ai was registered in 2017, before the company, and transferred on 2026-06-02 per RDAP. Every x.ai page except robots.txt and security.txt answered a Cloudflare block page (403) on 2026-11-06, as the legal pages did on 2026-10-06, so the contracting entity wasn't confirmed. The docs now use the name SpaceXSI and the status page SpaceXAI.", "endpointOnVendorDomain": true, "terms": "https://x.ai/legal/terms-of-service-enterprise", "privacy": "https://x.ai/legal/privacy-policy", "statusPage": "https://status.x.ai", "changelog": "https://docs.x.ai/developers/release-notes", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "x.ai/robots.txt allows all but /tools/, with Content-Signal ai-train=yes, search=yes, ai-input=yes. docs.x.ai allows all with ai-input=yes. The x.ai pages that robots.txt allows answered a Cloudflare 'Attention Required' page, which we did not try to get past.", "security.txt at x.ai/.well-known/security.txt is valid to 2027-06-29, with vulnerabilities@x.ai and abuse@x.ai." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/xai-api.json", "live": { "slug": "xai-api", "probe": { "target": "https://api.x.ai/v1", "method": "get", "lastAt": "2026-11-07T18:21:06.440217402Z", "lastOk": true, "lastStatus": 404, "lastMs": 122, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 178, "p95ms24h": 276, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "vendorStatus": { "page": "https://status.x.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:49:01.143662157Z" }, "versions": [ { "registry": "github", "name": "xai-org/xai-sdk-python", "version": "v1.21.0", "released": "2026-10-23", "seenAt": "2026-11-07T00:18:15.193708838Z" }, { "registry": "pypi", "name": "xai-sdk", "version": "1.21.0", "released": "2026-10-23", "seenAt": "2026-11-07T00:18:15.09038487Z" } ], "githubStars": 598, "pypiWeekly": 912149, "securityTxt": { "url": "https://x.ai/.well-known/security.txt", "state": "valid", "expires": "2027-06-29T00:00:00.000Z", "checkedAt": "2026-11-07T16:01:43.978620532Z" }, "llmsTxt": { "url": "https://docs.x.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:24.762831371Z" }, "pages": [ { "url": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:46.034096807Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "1238569c8142" }, { "url": "https://docs.x.ai/developers/migration/may-15-retirement", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:48.207542223Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "813d0e188a0e" }, { "url": "https://docs.x.ai/developers/release-notes", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:52.143682141Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "7b37cfaf2576" }, { "url": "https://docs.x.ai/developers/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:08:50.158330981Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a563de9617fe" }, { "url": "https://x.ai/legal/privacy-policy", "kind": "privacy", "status": 403, "checkedAt": "2026-11-07T14:38:04.991061235Z", "changedAt": "0001-01-01T00:00:00Z" }, { "url": "https://x.ai/legal/terms-of-service-enterprise", "kind": "terms", "status": 403, "checkedAt": "2026-11-07T14:38:09.200382604Z", "changedAt": "0001-01-01T00:00:00Z" } ], "updatedAt": "2026-11-07T18:21:06.440217402Z" } }, "edges": [ { "by": 33, "category": "security", "leads": "xai-api", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.", "b": "Model reading. Team API keys with ACLs per endpoint and per model, QPM and TPM caps, expiry, and create, rotate, disable and delete through the Management API, plus documented mTLS. GitHub secret scanning disables leaked keys and emails the owner (30). The security FAQ says SpaceXSI never trains on API inputs or outputs without explicit permission (20). Requests and responses are kept 30 days for abuse auditing, then deleted, and team admins can switch on zero data retention themselves, confirmed by an `x-zero-data-retention` header on every response (15). Console audit log and a Management API audit-events endpoint, plus optional per-key request logging (15). security.txt valid to 2027-06-29 with a HackerOne bug bounty and a separate safety contact for prompt-injection issues. SOC 2 Type 2 is claimed in the security FAQ with the reports behind an NDA in the trust centre, so 17 of 20. Remote MCP doesn't support `require_approval`, which the model checklist doesn't score but reviewers should see. New in October, a `guidelines` array lets the caller make the model decline nsfw, violence or profanity content, which the checklist doesn't score." }, "scores": { "a": 64, "b": 97 } }, { "by": 31, "category": "maintenance", "leads": "xai-api", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.", "b": "Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10)." }, "scores": { "a": 46, "b": 77 } }, { "by": 28, "category": "schema", "leads": "xai-api", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60.", "b": "OpenAPI 3.1 document at docs.x.ai/openapi.json, 39 paths and 205 schemas on 6 November, covering Responses, Chat Completions, files, images, videos and models. The batch endpoints documented in the REST reference still aren't in it (20 of 25, applied as for gemini-api's missing Interactions API). llms.txt and a Markdown twin of every page, plus a docs MCP server (10). The models page says which model to use for code, chat, images, video and voice, and reference pages list each parameter. Reference not read in full (18 of 20). Structured outputs are guaranteed to match the schema for supported keywords, and tool arguments always conform with `strict` implicitly true (15). Examples in Python, JavaScript and curl on every guide. The debugging page lists status codes with fixes, but the cause cells for 400, 403, 404 and 415 are still empty (13 of 15). Release notes are grouped by month without day dates, and model slugs come as aliases and dated versions (12 of 15)." }, "scores": { "a": 60, "b": 88 } }, { "by": 15, "category": "reliability", "leads": "xai-api", "name": "Reliability", "reasons": { "a": "No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40.", "b": "Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10)." }, "scores": { "a": 40, "b": 55 } }, { "by": 15, "category": "ergonomics", "leads": "xai-api", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75.", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15)." }, "scores": { "a": 75, "b": 90 } }, { "by": 10, "category": "transparency", "leads": "xai-api", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41.", "b": "Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20)." }, "scores": { "a": 53, "b": 63 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Meta", "b": "SpaceXSI (xAI)", "name": "Vendor" }, { "a": "https://api.meta.ai/v1", "b": "https://api.x.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.", "b": "Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-12", "b": "2026-11-02", "name": "Last release" }, { "a": "2026-10-02", "b": "2026-10-27", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "2026-10-27", "name": "Privacy policy last updated" }, { "a": "yes", "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": "not found in the text", "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": "none", "b": "597 stars, 912k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Meta Model API or xAI API (Grok)?" }, { "answer": "Both need an API key.", "question": "Do Meta Model API and xAI API (Grok) need an API key?" }, { "answer": "Yes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and xAI API (Grok) at https://api.x.ai/v1.", "question": "Can an agent call Meta Model API and xAI API (Grok) without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.", "slug": "meta-model-api", "watchFor": "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found" }, { "aheadOn": [ "Reliability, 55 against 40", "Schema \u0026 documentation, 88 against 60", "Agent ergonomics, 90 against 75", "Security \u0026 auth, 97 against 64", "Maintenance \u0026 community, 77 against 46", "Transparency \u0026 trust, 63 against 53" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.", "slug": "xai-api", "watchFor": "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August" } ], "history": { "meta-model-api": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 52.5, "fromGrade": "D", "to": 52.3, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 52.2, "fromGrade": "D", "to": 52.5, "toGrade": "D" } ], "xai-api": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api.json", "title": "Amazon Bedrock vs Meta Model API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.json", "title": "Amazon Bedrock vs xAI API (Grok)", "url": 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"https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.json", "title": "Meta Model API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json", "title": "Meta Model API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart.json", "title": "Meta Model API vs Simplismart", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json", "title": "Meta Model API vs StepFun API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash.json", "title": "Meta Model API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.json", "title": "Meta Model API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.json", "title": "Meta Model API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.json", "title": "Meta Model API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai.json", "title": "Meta Model API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api.json", "title": "MiniMax API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api.json", "title": "Mistral AI API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api.json", "title": "Muse Spark Open vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api.json", "title": "Nemotron 3.5 Super VL vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.json", "title": "Novita AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api.json", "title": "OpenAI API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api.json", "title": "OpenRouter vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api.json", "title": "Prism Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api.json", "title": "Router.com (Ramp Router) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json", "title": "Beam 1.0 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api.json", "title": "RouterPlus vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api.json", "title": "SambaCloud vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api.json", "title": "SiliconFlow vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api.json", "title": "Simplismart vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.json", "title": "StepFun API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api.json", "title": "SWE-2 Flash vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api.json", "title": "Tencent Cloud TokenHub vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api" }, { "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/vercel-ai-gateway-vs-xai-api.json", "title": "Vercel AI Gateway vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.json", "title": "Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api" } ], "panel": null, "scores": [ { "by": 15, "edge": "xai-api", "key": "reliability", "meta-model-api": 40, "name": "Reliability", "weight": 16, "xai-api": 55 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 28, "edge": "xai-api", "key": "schema", "meta-model-api": 60, "name": "Schema \u0026 documentation", "weight": 13, "xai-api": 88 }, { "by": 15, "edge": "xai-api", "key": "ergonomics", "meta-model-api": 75, "name": "Agent ergonomics", "weight": 13, "xai-api": 90 }, { "by": 33, "edge": "xai-api", "key": "security", "meta-model-api": 64, "name": "Security \u0026 auth", "weight": 14, "xai-api": 97 }, { "by": 0, "edge": "", "key": "payments", "meta-model-api": 20, "name": "Payments \u0026 pricing", "weight": 10, "xai-api": 20 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 31, "edge": "xai-api", "key": "maintenance", "meta-model-api": 46, "name": "Maintenance \u0026 community", "weight": 7, "xai-api": 77 }, { "by": 10, "edge": "xai-api", "key": "transparency", "meta-model-api": 53, "name": "Transparency \u0026 trust", "weight": 7, "xai-api": 63 } ], "summary": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in 6 of 7 scored categories. Both do llm inference.", "tasks": [ { "a": "$3.85", "b": "$21.76", "cheaper": "meta-model-api", "task": "Research a product and write a sourced report", "what": "muse-wonder-1.0 on Meta Model API, grok-4.7 on xAI API (Grok)" }, { "a": "$1.67", "b": "$4.85", "cheaper": "meta-model-api", "task": "Build a small four-page website", "what": "muse-wonder-1.0 on Meta Model API, grok-4.7 on xAI API (Grok)" }, { "a": "$0.37", "b": "$1.07", "cheaper": "meta-model-api", "task": "Find and fix a bug in a large codebase", "what": "muse-wonder-1.0 on Meta Model API, grok-4.7 on xAI API (Grok)" } ], "tutorials": [], "verdicts": { "meta-model-api": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.", "xai-api": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api", "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.min.md" }, "markdown": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Meta Model API: grade D, 52.3/100, rank #989 of 1486. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- xAI API (Grok): grade BB, 71.7/100, rank #151 of 1486. Markdown https://www.anchorterminal.com/tools/xai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/xai-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Meta Model API (D)\n\nGood for: Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\n\n### xAI API (Grok) (BB)\n\nGood for: Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.\n\nAhead on:\n- Reliability, 55 against 40\n- Schema \u0026 documentation, 88 against 60\n- Agent ergonomics, 90 against 75\n- Security \u0026 auth, 97 against 64\n- Maintenance \u0026 community, 77 against 46\n- Transparency \u0026 trust, 63 against 53\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August\n\n\n## Why the edge\n\n### Security \u0026 auth: xAI API (Grok) +33\n\n- Meta Model API (64): Model reading. Bearer keys per team, named, shown once and revoked by deletion, with rotation advice. No scopes, read-only keys or per-key limits found (20 of 30). The terms say Meta will not use Content submitted to the Standard Services to train Meta Models, and training applies only to the `-contributor` model IDs a caller picks. Content may still be used to develop and improve safety and security systems (17 of 20). Retention is 'as needed' for the service, the law, flagged violations and safety review, with no period stated. Zero data retention for qualified accounts through sales, with flagged content kept up to 2 years (10 of 15). The usage dashboard shows tokens and requests per day by model, with no per-key or per-call log found (5 of 15). No security.txt on dev.meta.ai. Meta's bug bounty at bugbounty.meta.com is named in the Muse Code SDK's security policy, and a security commitments page describes TLS 1.2 or later, PCI-DSS card handling and an ISMS, with no named certification for the API (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.\n- xAI API (Grok) (97): Model reading. Team API keys with ACLs per endpoint and per model, QPM and TPM caps, expiry, and create, rotate, disable and delete through the Management API, plus documented mTLS. GitHub secret scanning disables leaked keys and emails the owner (30). The security FAQ says SpaceXSI never trains on API inputs or outputs without explicit permission (20). Requests and responses are kept 30 days for abuse auditing, then deleted, and team admins can switch on zero data retention themselves, confirmed by an `x-zero-data-retention` header on every response (15). Console audit log and a Management API audit-events endpoint, plus optional per-key request logging (15). security.txt valid to 2027-06-29 with a HackerOne bug bounty and a separate safety contact for prompt-injection issues. SOC 2 Type 2 is claimed in the security FAQ with the reports behind an NDA in the trust centre, so 17 of 20. Remote MCP doesn't support `require_approval`, which the model checklist doesn't score but reviewers should see. New in October, a `guidelines` array lets the caller make the model decline nsfw, violence or profanity content, which the checklist doesn't score.\n\n### Maintenance \u0026 community: xAI API (Grok) +31\n\n- Meta Model API (46): Model reading. Muse Wonder launched on 12 October 2026 (30). No deprecation policy or notice period found. All three Muse Spark versions are still served, so no retirement has tested one (0 of 12). Dated launches on the API since 6 August that we read, Muse Image on 25 August, Muse Voice Transcribe on 3 September and Muse Wonder on 12 October (8 of 8). Muse Code leaving beta on 31 August is a separate product and isn't counted. No Model API changelog. A help centre with support tickets, answered 'typically within two business days' by Meta's own account, which we didn't test (8 of 15). No SDK of Meta's own for the API (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.\n- xAI API (Grok) (77): Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10).\n\n### Schema \u0026 documentation: xAI API (Grok) +28\n\n- Meta Model API (60): No OpenAPI or similar machine-readable contract found. The reference is Markdown pages with schema sections, and /openapi.json paths on dev.meta.ai return 404 (0). llms.txt at dev.meta.ai/llms.txt, and every docs page has a Markdown copy (10). The models page says when to choose Muse Wonder and when Muse Spark, and the tool-calling and structured-output guides state their limits, such as `tool_choice` only accepting `auto` and which schema keywords `strict` allows (16 of 20). JSON Schema tools and output, `reasoning_effort` an enum from minimal to max, a strict subset that returns 400 when violated, though `tool_choice` has one value (12 of 15). Curl, Python and TypeScript examples on each page and an error guide covering 400 to 504 with the error envelope, codes and a fix for each (15). Versioned model IDs (muse-spark-1.1 to 1.3, muse-wonder-1.0) and dated launch posts on the developer blog, but no API changelog (7 of 15). 0 + 10 + 16 + 12 + 15 + 7 = 60.\n- xAI API (Grok) (88): OpenAPI 3.1 document at docs.x.ai/openapi.json, 39 paths and 205 schemas on 6 November, covering Responses, Chat Completions, files, images, videos and models. The batch endpoints documented in the REST reference still aren't in it (20 of 25, applied as for gemini-api's missing Interactions API). llms.txt and a Markdown twin of every page, plus a docs MCP server (10). The models page says which model to use for code, chat, images, video and voice, and reference pages list each parameter. Reference not read in full (18 of 20). Structured outputs are guaranteed to match the schema for supported keywords, and tool arguments always conform with `strict` implicitly true (15). Examples in Python, JavaScript and curl on every guide. The debugging page lists status codes with fixes, but the cause cells for 400, 403, 404 and 415 are still empty (13 of 15). Release notes are grouped by month without day dates, and model slugs come as aliases and dated versions (12 of 15).\n\n### Reliability: xAI API (Grok) +15\n\n- Meta Model API (40): No status page with readable component history. The error guide's dev.meta.ai/status link now opens a Model API Status page, which showed \"Status information is unavailable\" to our reader on 4 November, its content drawn by script that we don't request, and the documented `GET /v1/status` reports only the current state (0). No readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-wonder-1.0, 150 RPM and 3,000,000 TPM for the contributor variants, 600 background submissions a minute (15). 429 and 503 carry Retry-After (60 seconds for `service_overloaded` and `backend_unavailable`), with backoff-with-jitter guidance, rate-limit headers on every token response and a documented mid-stream `server_shutting_down` event to retry, a generation call read as stateless as gemini-api's (15). No SLA found, and the terms let Meta throttle or suspend access without notice (0). Muse Wonder is labelled a preview. Muse Spark 1.3 carries no preview label, but the API opened on 8 July 2026 as a public preview and we found no general-availability notice, so half (5 of 10, the 12 October partial, kept). 0 + 5 + 15 + 15 + 0 + 5 = 40.\n- xAI API (Grok) (55): Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10).\n\n### Agent ergonomics: xAI API (Grok) +15\n\n- Meta Model API (75): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls on all three endpoints, parallel calls, tool search with deferred loading, built-in web search and a computer-use tool, but `tool_choice` accepts only `auto`, so a call can't be forced or forbidden (15 of 20). Output constrained to the JSON Schema on every surface (15). Automatic prompt caching with no setup, and cached input at 5 per cent of the input price on Muse Wonder (15). 1,048,576-token context on Muse Wonder and every Muse Spark version, with no long-context premium (15). No batch endpoint or discount found. Background responses run asynchronously at the normal price (0). No SDK of Meta's own. The docs use the OpenAI and Anthropic SDKs against compatible endpoints, the same reading as StepFun (0). OpenAI-style error envelope with `type` and `code`, per-status fixes and named retryable codes (15). 15 + 15 + 15 + 15 + 0 + 0 + 15 = 75.\n- xAI API (Grok) (90): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15).\n\n### Transparency \u0026 trust: xAI API (Grok) +10\n\n- Meta Model API (53): Closed service with clear terms, under California law with AAA arbitration for Meta Platforms, Inc. and Irish law and courts for Meta Platforms Ireland Limited, with liability capped at the greater of 12 months of fees or $1,000. Muse Glimmer's open weights don't change the hosted service (15). The terms, the models page, the pricing page and the zero-retention help page agree that Standard content isn't used for training and Contributor content may be, but retention periods are not stated outside zero retention, and the privacy policy is Meta's general one (18 of 30). No deprecation policy or dated notices found, and the terms let Meta remove functionality without notice (0). A subprocessor list is linked from the terms but wasn't read, and no data locations were found (8 of 20). 15 + 18 + 0 + 8 = 41.\n- xAI API (Grok) (63): Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20).\n\n## Score by category\n\n| Category | Weight | Meta Model API | xAI API (Grok) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 55 | xAI API (Grok) +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 88 | xAI API (Grok) +28 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 90 | xAI API (Grok) +15 |\n| Security \u0026 auth | 14% (17.5 this run) | 64 | 97 | xAI API (Grok) +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 77 | xAI API (Grok) +31 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 53 | 63 | xAI API (Grok) +10 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **52.3 · D** | **71.7 · BB** | |\n\n## Facts side by side\n\n| Fact | Meta Model API | xAI API (Grok) |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | SpaceXSI (xAI) |\n| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.x.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party. | Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-12 | 2026-11-02 |\n| Terms last updated | 2026-10-02 | 2026-10-27 |\n| Privacy policy last updated | couldn't be read | 2026-10-27 |\n| Customer content may train models | yes | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\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 | none | 597 stars, 912k PyPI/wk |\n\n## What the same task costs\n\n| Task | Meta Model API | xAI API (Grok) |\n| --- | --- | --- |\n| Research a product and write a sourced report | $3.85 | $21.76 |\n| Build a small four-page website | $1.67 | $4.85 |\n| Find and fix a bug in a large codebase | $0.37 | $1.07 |\n\n## How the scores have moved\n\n### Meta Model API\n\n- -0.2 on 30 October 2026: checklist\n- +0.3 on 27 October 2026: checklist\n\n### xAI API (Grok)\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Meta Model API.** Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.\n\n**xAI API (Grok).** Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.\n\n## Before you call either\n\n### Meta Model API\n\n1. Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests\n2. Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content\n3. Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key\n4. Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`\n5. Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported\n\n### xAI API (Grok)\n\n1. Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated\n2. Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price\n3. Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2\n4. Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context\n5. Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6\n\n## Questions\n\n### Which is better for AI agents, Meta Model API or xAI API (Grok)?\n\nxAI API (Grok) scores 71.7 (BB) on agent readiness against Meta Model API's 52.3 (D), and leads in 6 of 7 scored categories.\n\n### Do Meta Model API and xAI API (Grok) need an API key?\n\nBoth need an API key.\n\n### Can an agent call Meta Model API and xAI API (Grok) without installing anything?\n\nYes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and xAI API (Grok) at https://api.x.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"meta-model-api\", \"b\": \"xai-api\"}`. 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