Meta Model API vs xAI API (Grok)

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.

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.

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.

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).

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.

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).

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.

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).

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.

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).

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.

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).