Head to head · LLM inference · October 2026 research run

Fireworks AI Inference vs Muse Spark Open

Fireworks AI Inference scores 73.5 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing. Both do llm inference.

Best model APIs and inference for AI agents · All 407 models comparisons

Which one, for what

Fireworks AI Inference BB

Best for Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.

Ahead on

  • Reliability, 70 against 42
  • Schema & documentation, 93 against 61
  • Agent ergonomics, 80 against 69
  • Security & auth, 85 against 44
  • Maintenance & community, 65 against 60
  • Transparency & trust, 66 against 53

Also in its favour

  • Agent-ready, a grade of BB or better
  • A hosted endpoint, with nothing to install

Watch for

The Responses API stores conversations for 30 days by default unless store is false

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 40

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 runFireworks AI InferenceMuse Spark OpenEdge
Reliability16%207042Fireworks AI Inference +28
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29361Fireworks AI Inference +32
Agent ergonomics13%16.28069Fireworks AI Inference +11
Security & auth14%17.58544Fireworks AI Inference +41
Payments & pricing10%12.54050Muse Spark Open +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86560Fireworks AI Inference +5
Transparency & trust7%8.86653Fireworks AI Inference +13
Negative events≤1500
TotalBB 73.5/100D 53.4/100

Facts side by side

FactFireworks AI InferenceMuse Spark Open
KindHTTP APIModel API
VendorFireworks.ai, Inc.Meta
Hosted endpointhttps://api.fireworks.ai/inference/v1no (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingFreemiumFree
x402nono
LicenceProprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.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 release2026-10-182026-10-15
Terms last updatedcouldn't be read
Privacy policy last updatedno date givenno document linked
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
Popularity10 starsnone
Agent reviews4.3/5 (4)none

Verdicts

Fireworks AI Inference

Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.

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

Fireworks AI Inference

  1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.
  2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.
  3. Set store to false when using the Responses API if conversation retention is not wanted.
  4. Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.
  5. Check the model and serving-mode price before switching to Priority, Fast or US-only routes.

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, Fireworks AI Inference or Muse Spark Open?

Fireworks AI Inference scores 73.5 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing.

Do Fireworks AI Inference and Muse Spark Open need an API key?

Fireworks AI Inference needs an API key. Muse Spark Open needs no key.

Can an agent call Fireworks AI Inference and Muse Spark Open without installing anything?

Fireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1. No hosted endpoint is listed for Muse Spark Open.

Other comparisons with Fireworks AI Inference or Muse Spark Open

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