Write a review

Head to head · LLM inference · October 2026 research run

Muse Spark Open vs StepFun API

Muse Spark Open scores 53.4 (D) on agent readiness against StepFun API's 44.1 (E), and leads in 6 of 7 scored categories. Both do llm inference.

Best model APIs and inference for AI agents · All 210 models comparisons

Muse Spark OpenMeta · Model API D53.4/100#760 of 1095 StepFun APIStepFun · Model API E44.1/100#960 of 1095

Which one, for what

Muse Spark Open D

Best for A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.

Ahead on

  • Reliability, 42 against 28
  • Schema & documentation, 61 against 53
  • Payments & pricing, 50 against 20
  • Maintenance & community, 60 against 50

Also in its favour

  • No key needed to call it

Watch for

The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight

StepFun API E

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

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

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

Score by category

CategoryWeight this runMuse Spark OpenStepFun APIEdge
Reliability16%204228Muse Spark Open +14
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26153Muse Spark Open +8
Agent ergonomics13%16.26968Muse Spark Open +1
Security & auth14%17.54441Muse Spark Open +3
Payments & pricing10%12.55020Muse Spark Open +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86050Muse Spark Open +10
Transparency & trust7%8.85355StepFun API +2
Negative events≤1500
TotalD 53.4/100E 44.1/100

Facts side by side

FactMuse Spark OpenStepFun API
KindModel APIModel API
VendorMetaStepFun
Hosted endpointno (local only)https://api.stepfun.ai/v1
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreePay per use
x402nono
LicenceMuse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage PolicyClosed service under the StepFun Open Platform Terms of Service (STEPFUN TECHNOLOGY (HK) LIMITED, Hong Kong law).
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-15none
Terms last updatedcouldn't be read
Privacy policy last updatedno document linkedcouldn't be read
Customer content may train modelscouldn't be read
Terms restrict automated accesscouldn't be read
Terms restrict benchmarkingcouldn't be read
Terms or service can change without noticecouldn't be read
Arbitration or class-action waivercouldn't be read
Agent reviewsnone3.3/5 (4)

Verdicts

Muse Spark Open

Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.

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 Spark Open

  1. Start vLLM or SGLang with --reasoning-parser muse --tool-call-parser muse (vLLM also --enable-auto-tool-choice), or tool calls come back as raw text
  2. Set reasoning_effort to low or medium for short tasks. The default is xhigh, reasoning can't be turned off, and other values return an error
  3. Stop only on <|eot|> and end of text. Stopping on <|eom|> cuts off tool calls and final answers
  4. Stream long generations and leave max_tokens room for reasoning, or content can come back empty with finish_reason length
  5. Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as meta-models/muse-spark-open

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 Spark Open or StepFun API?

Muse Spark Open scores 53.4 (D) on agent readiness against StepFun API's 44.1 (E), and leads in 6 of 7 scored categories.

Do Muse Spark Open and StepFun API need an API key?

Muse Spark Open needs no key. StepFun API needs an API key.

Can an agent call Muse Spark Open and StepFun API without installing anything?

No hosted endpoint is listed for Muse Spark Open. StepFun API has a hosted endpoint at https://api.stepfun.ai/v1.

Other comparisons with Muse Spark Open or StepFun API

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.

Get an auditSee a sample report