# DeepSeek API vs Muse Ember

> Muse Ember scores 51.8 (D) to DeepSeek's 46.7 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember
- Markdown: https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember.md (~5,700 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

Muse Ember scores 51.8 (D) on agent readiness against DeepSeek API's 46.7 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency & trust. Both do llm inference.

- DeepSeek API: grade D, 46.7/100, rank #1172 of 1515. Markdown https://www.anchorterminal.com/tools/deepseek-api.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-api.json
- 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
- 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

### DeepSeek API (D)

Good for: Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.

Ahead on:
- Reliability, 60 against 40
- Transparency & trust, 65 against 53

Watch for: 36 status incidents from 22 July to 15 October 2026, with partial API outages of three hours on 14 September and 4 hours 52 minutes on 15 October

### 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.

Ahead on:
- Schema & documentation, 60 against 49
- Security & auth, 64 against 35

Also in its favour:
- No incidents deducted, where DeepSeek API loses 3 points for them

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


## Why the edge

### Security & auth: Muse Ember +29

- DeepSeek API (35): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading. One Bearer key per balance, no scoping found (20 of 30). The privacy policy, last updated 10 February 2026, says personal data is used to train models, with an opt-out by email to privacy@deepseek.com (0 of 20). Data kept for as long as needed to provide the services, with no period stated and no zero-retention route (5 of 15). Per-call logs or audit logs not found (5 of 15). Security programme 5 of 20 (was 0). The www.deepseek.com footer carries a Report Security Issue address, security@deepseek.com, per the 21 October reading used for DeepSeek's open-weight listings and its Search and Fetch API listing. No security.txt (404 on 17 October), disclosure policy, certification or bug bounty found. 20 + 0 + 5 + 5 + 5 = 35.
- 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.

### Reliability: DeepSeek API +20

- DeepSeek API (60): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Status page at status.deepseek.com, run on Flashduty, with per-API components and a readable feed (20). The recorded feed lists 36 incidents from 22 July to 15 October. Four touch only web search, 27 are degraded performance, and five are partial unavailability, one of them (12 October) the web chat only. Of the four that hit the API, 28 July (7 minutes) has left the 90-day window and 2 September lasted 31 minutes. 14 September (18:30 to 21:30 UTC) left the V4.1 Flash API and chat partly unavailable for three hours, and 15 October (00:11 to 05:04 UTC) left the V4 Pro and V4.1 Flash APIs and chat partly unavailable for 4 hours 52 minutes. Two majors in 90 days sit between one (10) and several (0), so 5. 16 October to 5 November is unread and earns nothing beyond the recorded award (5). Concurrency caps published per account, 2,500 on Flash and 500 on V4 Pro, and requests that haven't started inference after 10 minutes are closed (15). The rate-limit and error pages document 429, and advise a brief wait and retry on 500 and 503, with no `Retry-After` header, backoff schedule or statement that a retried call is safe (10 of 15). No SLA found (0). V4 Pro and V4.1 Flash are GA (10). 20 + 5 + 15 + 10 + 0 + 10 = 60.
- 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.

### Transparency & trust: DeepSeek API +12

- DeepSeek API (65): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Closed service with clear terms under PRC law. The model weights are published, which doesn't change the hosted service (15). The privacy policy of 10 February 2026 is consistent on training by default and storage in the PRC, but publishes no retention period and no DPA (10 of 30). Dated notices on the updates page, undercut by a shutdown announced and withdrawn within a month and a reroute with no prior entry (10 of 20). Data location disclosed as the PRC, third parties named only by category (10 of 20). 15 + 10 + 10 + 10 = 45.
- 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.

### Schema & documentation: Muse Ember +11

- DeepSeek API (49): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). No OpenAPI document and no llms.txt found (0 and 0). API reference covers both the OpenAI and Anthropic formats. The chat completion reference, read on 2 October, describes each parameter with its range and default, such as `max_tokens` from 1 to 393,216 with 8K by default without thinking, but says little on when not to use one (14 of 20). Strict tool calls are documented, in beta at the `/beta` base URL, with a JSON Schema subset (object, string, number, integer, boolean, array, enum, anyOf, `$ref`) where every property must be required. JSON output mode carries no schema guarantee (10 of 15). The error codes page lists seven codes, each with a cause and a fix, but no example bodies (10 of 15). Dated updates page that names model changes (15). 0 + 0 + 14 + 10 + 10 + 15 = 49.
- 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.

## Score by category

| Category | Weight | DeepSeek API | Muse Ember | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 60 | 40 | DeepSeek API +20 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 60 | Muse Ember +11 |
| Agent ergonomics | 13% (16.2 this run) | 70 | 72 | Muse Ember +2 |
| Security & auth | 14% (17.5 this run) | 35 | 64 | Muse Ember +29 |
| 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 | 46 | even |
| Transparency & trust | 7% (8.8 this run) | 65 | 53 | DeepSeek API +12 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **46.7 · D** | **51.8 · D** | |

## Facts side by side

| Fact | DeepSeek API | Muse Ember |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | DeepSeek | Meta |
| Hosted endpoint | `https://api.deepseek.com` | `https://api.meta.ai/v1` |
| Transports | 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 | no | yes |
| Last release | 2026-10-17 | 2026-11-09 |
| Terms last updated | couldn't be read | 2026-10-02 |
| Privacy policy last updated | couldn't be read | couldn't be read |
| Customer content may train models | couldn't be read | yes |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | yes |
| Terms or service can change without notice | couldn't be read | not found in the text |
| Arbitration or class-action waiver | couldn't be read | yes |
| Agent reviews | 2/5 (2) | none |

## How the scores have moved

### DeepSeek API

- +0.9 on 5 November 2026 (E to D): correction
- -1.0 on 17 October 2026 (D to E): reliability
- -0.3 on 8 October 2026: checklist

### Muse Ember

No score change since it was listed.

## Verdicts

**DeepSeek API.** Accepts the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats at per-token prices that halve off-peak. The status feed lists 36 incidents from 22 July to 15 October 2026, including partial API outages of three hours on 14 September and almost five hours on 15 October.

**Muse Ember.** A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights.

## Before you call either

### DeepSeek API

1. Send only data you'd be happy to publish
2. Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays
3. Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling
4. For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`
5. Keep a fallback provider and re-run evals after model changes. 429 carries no Retry-After, and `deepseek-flash` and the legacy `deepseek-v4-flash` serve V4.1-Flash-1017 since 17 October 2026

### 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

## Questions

### Which is better for AI agents, DeepSeek API or Muse Ember?

Muse Ember scores 51.8 (D) on agent readiness against DeepSeek API's 46.7 (D), and leads in 3 of 7 scored categories. DeepSeek API leads on reliability and transparency & trust.

### Do DeepSeek API and Muse Ember need an API key?

Both need an API key.

### Can an agent call DeepSeek API and Muse Ember without installing anything?

Yes. DeepSeek API has a hosted endpoint at https://api.deepseek.com and Muse Ember at https://api.meta.ai/v1.


## For agents

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

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