Head to head · LLM inference · October 2026 research run
Eden AI vs Muse Ember
Eden AI scores 59.9 (C) on agent readiness against Muse Ember's 51.8 (D), and leads in 6 of 7 scored categories. Muse Ember leads on reliability. Both do llm inference.
Best model APIs and inference for AI agents · All 871 models comparisons
Which one, for what
Eden AI C
Best for Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.
Ahead on
- Schema & documentation, 81 against 60
- Security & auth, 82 against 64
- Payments & pricing, 30 against 20
- Maintenance & community, 58 against 46
Watch for
No public status page, incident history or SLA found
Best 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.
Ahead on
- Reliability, 40 against 33
Watch for
No weights and no parameter count published, so it can't be run locally
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Schema & documentation Eden AI +21
Eden AI 81
Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.
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.
Security & auth Eden AI +18
Eden AI 82
Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.
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.
Maintenance & community Eden AI +12
Eden AI 58
Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.
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.
Payments & pricing Eden AI +10
Eden AI 30
No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.
Muse Ember 20
Published rubric. No payment protocol (0). Per-token prices for both tiers published without a login, read 9 November (20). No free API allowance found; billing needs a card, per the platform reading (0). Browser sign-up (0). 0 + 20 + 0 + 0 = 20.
Reliability Muse Ember +7
Eden AI 33
Router, read on the hosted lines. No status page is linked from the site or docs, and status.edenai.co didn't resolve for us on 6 November 2026 (0). No incident history to read (5). The rate-limits page gives 10 requests a second per account, shared across keys, while the plans page gives 7 a second, raisable to 15, so the figure is documented but inconsistent (10). Fallback retries the next model or provider on a 429 or error inside one request, but no client-facing 429 or Retry-After guidance was found (8). No SLA published; 'Dedicated support & SLA' is listed only for the custom Advanced plan, and the pricing page's '99.99%' uptime is a claim without a status page behind it (0). The v3 API is GA (10). 0+5+10+8+0+10 = 33.
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.
Score by category
| Category | Weight this run | Eden AI | Muse Ember | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 33 | 40 | Muse Ember +7 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 81 | 60 | Eden AI +21 |
| Agent ergonomics | 13%16.2 | 75 | 72 | Eden AI +3 |
| Security & auth | 14%17.5 | 82 | 64 | Eden AI +18 |
| Payments & pricing | 10%12.5 | 30 | 20 | Eden AI +10 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 58 | 46 | Eden AI +12 |
| Transparency & trust | 7%8.8 | 55 | 53 | Eden AI +2 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 59.9/100 | D 51.8/100 |
Facts side by side
| Fact | Eden AI | Muse Ember |
|---|---|---|
| Kind | Model router | Model API |
| Vendor | Eden AI SAS | Meta |
| Hosted endpoint | https://mcp.edenai.run/mcp | https://api.meta.ai/v1 |
| Transports | HTTP, Streamable HTTP | |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | none | 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 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-05 | 2026-11-09 |
| Terms last updated | 2026-10-22 | 2026-10-02 |
| Privacy policy last updated | 2026-10-22 | couldn't be read |
| Customer content may train models | not found in the text | yes |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
Verdicts
Eden AI
Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.
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.
Before you call either
Eden AI
- Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them
- Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed
- Set max_tokens to 500 or more for reasoning models, or the answer can come back empty
- Pass a fallbacks list so a provider 429 or error retries inside one request
- Poll check_job for MCP tools marked long-running instead of calling them again
Muse Ember
- Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY
- Set the effort explicitly, reasoning.effort on Responses or reasoning_effort on Chat Completions. It defaults to max, and none isn't accepted; minimal or low suits classification and routing
- Keep input under 200K tokens a request, cached tokens and previous_response_id history included, or the whole request bills at the long-context rate
- Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises
- Use strict structured output for extraction and routing steps
- In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide
Questions
Which is better for AI agents, Eden AI or Muse Ember?
Eden AI scores 59.9 (C) on agent readiness against Muse Ember's 51.8 (D), and leads in 6 of 7 scored categories. Muse Ember leads on reliability.
Do Eden AI and Muse Ember need an API key?
Both need an API key.
Can an agent call Eden AI and Muse Ember without installing anything?
Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and Muse Ember at https://api.meta.ai/v1.
Other comparisons with Eden AI or Muse Ember
- Amazon Bedrock vs Eden AI
- Amazon Bedrock vs Muse Ember
- Claude API vs Eden AI
- Claude API vs Muse Ember
- Antseed vs Muse Ember
- Azure OpenAI in Foundry Models vs Eden AI
- Azure OpenAI in Foundry Models vs Muse Ember
- BlockRun.AI vs Eden AI
- BlockRun.AI vs Muse Ember
- Cerebras Inference vs Eden AI
- Cerebras Inference vs Muse Ember
- Cloudflare AI Gateway vs Eden AI
- Cloudflare AI Gateway vs Muse Ember
- Cloudflare Workers AI vs Eden AI
- Cloudflare Workers AI vs Muse Ember
- Cohere Chat API (Command models) vs Eden AI
- Cohere Chat API (Command models) vs Muse Ember
- DeepInfra vs Eden AI
- DeepInfra vs Muse Ember
- DeepSeek API vs Eden AI
- DeepSeek API vs Muse Ember
- Eden AI vs Glimpse
- Eden AI vs Fireworks AI Inference
- Eden AI vs Gemini Developer API
- Eden AI vs GroqCloud
- Eden AI vs Inkling 2 Small
- Eden AI vs Jais 3
- Eden AI vs Meta Model API
- Eden AI vs MiniMax API
- Eden AI vs Mistral AI API
- Eden AI vs Muse Spark Open
- Eden AI vs Nemotron 3.5 Super VL
- Eden AI vs Novita AI
- Eden AI vs OpenAI API
- Eden AI vs Prism Inference
- Eden AI vs Beam 1.0
- Eden AI vs SambaCloud
- Eden AI vs SiliconFlow
- Eden AI vs Simplismart
- Eden AI vs StepFun API
- Eden AI vs SWE-2 Flash
- Eden AI vs Together AI Inference
- Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)
- Eden AI vs xAI API (Grok)
- Glimpse vs Muse Ember
- Fireworks AI Inference vs Muse Ember
- Gemini Developer API vs Muse Ember
- GroqCloud vs Muse Ember
- Hugging Face Inference Providers vs Muse Ember
- Inkling 2 Small vs Muse Ember
- Jais 3 vs Muse Ember
- Meta Model API vs Muse Ember
- MiniMax API vs Muse Ember
- Mistral AI API vs Muse Ember
- Muse Ember vs Muse Spark Open
- Muse Ember vs Nemotron 3.5 Super VL
- Muse Ember vs Novita AI
- Muse Ember vs OpenAI API
- Muse Ember vs OpenRouter
- Muse Ember vs Prism Inference
- Muse Ember vs Router.com (Ramp Router)
- Muse Ember vs Beam 1.0
- Muse Ember vs RouterPlus
- Muse Ember vs SambaCloud
- Muse Ember vs SiliconFlow
- Muse Ember vs Simplismart
- Muse Ember vs StepFun API
- Muse Ember vs SWE-2 Flash
- Muse Ember vs Tencent Cloud TokenHub
- Muse Ember vs Together AI Inference
- Muse Ember vs Vercel AI Gateway
- Muse Ember vs Vertex AI (Gemini Enterprise Agent Platform)
- Muse Ember vs xAI API (Grok)
- Antseed vs Eden AI
- Eden AI vs Hugging Face Inference Providers
- Eden AI vs LiteLLM
- Eden AI vs OpenRouter
- Eden AI vs Router.com (Ramp Router)
- Eden AI vs RouterPlus
- Eden AI vs Tencent Cloud TokenHub
- Eden AI vs Vercel AI Gateway
Machine-readable
- This page as Markdown
/compare/eden-ai-vs-muse-ember.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/eden-ai.json·/api/v1/tools/muse-ember.json - From a terminal
anchor compare eden-ai muse-ember(the CLI) - Over MCP
compare_tools {"a": "eden-ai", "b": "muse-ember"}at/mcp, no key