# Muse Ember vs xAI API (Grok)

> xAI scores 71.7 (BB) to Muse Ember's 51.8 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/muse-ember-vs-xai-api
- Markdown: https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.md (~6,450 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-09

xAI API (Grok) scores 71.7 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in 6 of 7 scored categories. Both do llm inference.

- 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
- xAI API (Grok): grade BB, 71.7/100, rank #152 of 1515. Markdown https://www.anchorterminal.com/tools/xai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/xai-api.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 871 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Muse Ember (D)

Good 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.

Watch for: No weights and no parameter count published, so it can't be run locally

### xAI API (Grok) (BB)

Good 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.

Ahead on:
- Reliability, 55 against 40
- Schema & documentation, 88 against 60
- Agent ergonomics, 90 against 72
- Security & auth, 97 against 64
- Maintenance & community, 77 against 46
- Transparency & trust, 63 against 53

Also in its favour:
- Agent-ready, a grade of BB or better

Watch 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


## Why the edge

### Security & auth: xAI API (Grok) +33

- 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.
- 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.

### Maintenance & community: xAI API (Grok) +31

- 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.
- 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).

### Schema & documentation: xAI API (Grok) +28

- 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.
- 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).

### Agent ergonomics: xAI API (Grok) +18

- 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.
- 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).

### Reliability: xAI API (Grok) +15

- 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.
- 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).

### Transparency & trust: xAI API (Grok) +10

- 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.
- 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).

## Score by category

| Category | Weight | Muse Ember | xAI API (Grok) | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 40 | 55 | xAI API (Grok) +15 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 60 | 88 | xAI API (Grok) +28 |
| Agent ergonomics | 13% (16.2 this run) | 72 | 90 | xAI API (Grok) +18 |
| Security & auth | 14% (17.5 this run) | 64 | 97 | xAI API (Grok) +33 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 46 | 77 | xAI API (Grok) +31 |
| Transparency & trust | 7% (8.8 this run) | 53 | 63 | xAI API (Grok) +10 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **51.8 · D** | **71.7 · BB** | |

## Facts side by side

| Fact | Muse Ember | xAI API (Grok) |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Meta | SpaceXSI (xAI) |
| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.x.ai/v1` |
| Transports |  | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | 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 | Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-09 | 2026-11-02 |
| Terms last updated | 2026-10-02 | 2026-10-27 |
| Privacy policy last updated | couldn't be read | 2026-10-27 |
| Customer content may train models | yes | yes |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | yes |
| Popularity | none | 597 stars, 912k PyPI/wk |

## Verdicts

**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.

**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.

## Before you call either

### Muse Ember

1. Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY
2. 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
3. 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
4. Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises
5. Use strict structured output for extraction and routing steps
6. In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide

### xAI API (Grok)

1. Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated
2. Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price
3. Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2
4. Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context
5. 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

## Questions

### Which is better for AI agents, Muse Ember or xAI API (Grok)?

xAI API (Grok) scores 71.7 (BB) on agent readiness against Muse Ember's 51.8 (D), and leads in 6 of 7 scored categories.

### Do Muse Ember and xAI API (Grok) need an API key?

Both need an API key.

### Can an agent call Muse Ember and xAI API (Grok) without installing anything?

Yes. Muse Ember has a hosted endpoint at https://api.meta.ai/v1 and xAI API (Grok) at https://api.x.ai/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "muse-ember", "b": "xai-api"}`. From a terminal: `anchor compare muse-ember xai-api`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/muse-ember.json and https://www.anchorterminal.com/api/v1/tools/xai-api.json

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