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Head to head · LLM inference · October 2026 research run

Meta Model API vs Muse Spark Open

Muse Spark Open scores 53.4 (D) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security & auth. Both do llm inference.

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

Meta Model APIMeta · Model API D52.2/100#794 of 1095 Muse Spark OpenMeta · Model API D53.4/100#760 of 1095

Which one, for what

Meta Model API D

Best for Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.

Ahead on

  • Agent ergonomics, 75 against 69
  • Security & auth, 64 against 44

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

Muse Wonder is labelled a preview, and no deprecation policy or notice period was found

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

  • Payments & pricing, 50 against 20
  • Maintenance & community, 60 against 46

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

Score by category

CategoryWeight this runMeta Model APIMuse Spark OpenEdge
Reliability16%204042Muse Spark Open +2
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26061Muse Spark Open +1
Agent ergonomics13%16.27569Meta Model API +6
Security & auth14%17.56444Meta Model API +20
Payments & pricing10%12.52050Muse Spark Open +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84660Muse Spark Open +14
Transparency & trust7%8.85253Muse Spark Open +1
Negative events≤1500
TotalD 52.2/100D 53.4/100

Facts side by side

FactMeta Model APIMuse Spark Open
KindModel APIModel API
VendorMetaMeta
Hosted endpointhttps://api.meta.ai/v1no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingPay per useFree
x402nono
LicenceClosed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.Muse 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 Policy
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-122026-10-15
Terms last updated
Privacy policy last updatedcouldn't be readno document linked
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver

Verdicts

Meta Model API

Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.

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.

Before you call either

Meta Model API

  1. Use muse-wonder-1.0 for long multi-step work and muse-spark-1.3 for cheaper, high-volume calls. Both take the same requests
  2. Keep personal or confidential data away from -contributor model IDs. Meta may train on that content
  3. Honour Retry-After on 429 and 503, which is 60 seconds for service_overloaded, and check GET https://api.meta.ai/v1/status, which needs no key
  4. Pass the key to the OpenAI SDK explicitly or set OPENAI_API_KEY. The SDK doesn't read MODEL_API_KEY
  5. Leave tool_choice at auto. The docs say none and required are not supported

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

Questions

Which is better for AI agents, Meta Model API or Muse Spark Open?

Muse Spark Open scores 53.4 (D) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security & auth.

Do Meta Model API and Muse Spark Open need an API key?

Meta Model API needs an API key. Muse Spark Open needs no key.

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

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

Other comparisons with Meta Model API or Muse Spark Open

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