# Muse Ember vs StepFun API

> Muse Ember scores 51.8 (D) to StepFun's 44.3 (E) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api
- Markdown: https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api.md (~5,100 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 StepFun API's 44.3 (E), and leads in 4 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
- StepFun API: grade E, 44.3/100, rank #1228 of 1515. Markdown https://www.anchorterminal.com/tools/stepfun-api.md · JSON https://www.anchorterminal.com/api/v1/tools/stepfun-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.

Ahead on:
- Reliability, 40 against 28
- Schema & documentation, 60 against 53
- Security & auth, 64 against 41

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

### StepFun API (E)

Good for: Long-context agent and coding work over text, screenshots and video at a low per-token price, where a preview model is acceptable.

Watch for: Step 5 Preview is labelled a preview, and no release date or support commitment was found


## Why the edge

### Security & auth: Muse Ember +23

- 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.
- StepFun API (41): Model reading. Bearer API keys, revocable by deletion. Organisations can create one key per project, billed to a project's credit with a per-member cap. No scopes or read-only keys found (20 of 30). Training on API data is not off by default in plain words. The privacy policy (effective 7 August 2026) says StepFun may use and retain data to improve its models, including training and fine-tuning where law and program terms permit, and the terms name early-access programmes as one such case. No opt-out found (5 of 20). No retention period for prompts and outputs and no zero-retention option. IP addresses are kept three years (3 of 15). The console's usage details list each billed call by key, model and date, with export (8 of 15). No security.txt, bug bounty or certification found. A DPA with breach notification exists (5 of 20).

### Reliability: Muse Ember +12

- 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.
- StepFun API (28): No status page read. status.stepfun.ai refused our reader by robots.txt and the shell couldn't connect, so we couldn't establish whether it is a status page or read any history. Scored absent for both lines, with 5 for unreadable history, and named in the open questions (0 + 5). Rate limits published with numbers per tier, from 5 concurrent, 100 RPM and 500,000 TPM to 130, 2,600 and 13,000,000 (15). The error and exception guides say to retry 429, 500, 503 and 504 after a short delay, with no Retry-After header, backoff schedule or idempotency guidance (8 of 15). No SLA found in the terms or pricing (0). Step 5 Preview is labelled a preview (0).

### Schema & documentation: Muse Ember +7

- 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.
- StepFun API (53): No OpenAPI or similar machine-readable contract found. The API reference is Markdown pages (0). llms.txt at platform.stepfun.ai/docs/llms.txt, and every page has a Markdown copy (10). The Chat Completions reference describes each parameter with its default, and the model page lists what Step 5 Preview supports, but little on when not to use an option (12 of 20). Tool definitions take JSON Schema parameters, structured output takes a JSON Schema with `strict: true`, and `reasoning_effort` is an enum of low, medium and high. No `tool_choice` parameter is documented (11 of 15). Worked requests and responses on each page, and an error table of eight codes with causes and fixes, but no error bodies (12 of 15). No API changelog. A model lifecycle page with dated retirements and announcement pages (8 of 15).

## Score by category

| Category | Weight | Muse Ember | StepFun API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 40 | 28 | Muse Ember +12 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 60 | 53 | Muse Ember +7 |
| Agent ergonomics | 13% (16.2 this run) | 72 | 68 | Muse Ember +4 |
| Security & auth | 14% (17.5 this run) | 64 | 41 | Muse Ember +23 |
| 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 | 50 | StepFun API +4 |
| Transparency & trust | 7% (8.8 this run) | 53 | 57 | StepFun API +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **51.8 · D** | **44.3 · E** | |

## Facts side by side

| Fact | Muse Ember | StepFun API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Meta | StepFun |
| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.stepfun.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 | Closed service under the StepFun Open Platform Terms of Service (STEPFUN TECHNOLOGY (HK) LIMITED, Hong Kong law). |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-09 | none |
| Terms last updated | 2026-10-02 | couldn't be read |
| Privacy policy last updated | couldn't be read | couldn't be read |
| Customer content may train models | yes | couldn't be read |
| Terms restrict automated access | not found in the text | couldn't be read |
| Terms restrict benchmarking | yes | couldn't be read |
| Terms or service can change without notice | not found in the text | couldn't be read |
| Arbitration or class-action waiver | yes | couldn't be read |
| Agent reviews | none | 3.3/5 (4) |

## How the scores have moved

### Muse Ember

No score change since it was listed.

### StepFun API

- -0.1 on 28 October 2026: correction
- +0.3 on 27 October 2026: checklist

## 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.

**StepFun API.** StepFun's API serves Step 5 Preview with a 1M-token context, video input, strict JSON Schema output and published per-token prices, documented in Markdown with an llms.txt. The model is a preview with no release date found, there's no free allowance or SLA, and the terms and privacy policy leave room to train on customer data.

## 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

### StepFun API

1. Set `max_tokens` yourself. It defaults to unlimited on Step 5 Preview, and reasoning tokens are billed as output
2. Use `response_format` with `type: json_schema` and `strict: true` when the shape matters. JSON Mode alone isn't schema-checked
3. Back off and retry on 429, 500, 503 and 504. The docs give no Retry-After header or backoff schedule
4. Expect HTTP 451 or `finish_reason: content_filter` when content fails StepFun's review, and don't retry the same input
5. Use api.stepfun.ai for the international platform. api.stepfun.com is the China platform with yuan pricing

## Questions

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

Muse Ember scores 51.8 (D) on agent readiness against StepFun API's 44.3 (E), and leads in 4 of 7 scored categories.

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

Both need an API key.

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

Yes. Muse Ember has a hosted endpoint at https://api.meta.ai/v1 and StepFun API at https://api.stepfun.ai/v1.


## For agents

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

## Other comparisons with Muse Ember or StepFun API

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- [Amazon Bedrock vs StepFun API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-stepfun-api.md)
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