Head to head · LLM inference · October 2026 research run

DeepInfra vs Muse Spark Open

DeepInfra scores 63 (B) 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 210 models comparisons

Which one, for what

DeepInfra B

Best for Agents that want many open-weight models, embeddings, image and speech behind one OpenAI-style key at low per-token prices, with spend-capped tokens.

Ahead on

  • Reliability, 70 against 42
  • Schema & documentation, 69 against 61
  • Agent ergonomics, 77 against 69
  • Security & auth, 64 against 44
  • Maintenance & community, 65 against 60
  • Transparency & trust, 67 against 53

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

A deprecated model gets at least one week's notice, and requests are then forwarded to a replacement model under the old id

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

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 runDeepInfraMuse Spark OpenEdge
Reliability16%207042DeepInfra +28
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26961DeepInfra +8
Agent ergonomics13%16.27769DeepInfra +8
Security & auth14%17.56444DeepInfra +20
Payments & pricing10%12.52050Muse Spark Open +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86560DeepInfra +5
Transparency & trust7%8.86753DeepInfra +14
Negative events≤1500
TotalB 63/100D 53.4/100

Facts side by side

FactDeepInfraMuse Spark Open
KindModel APIModel API
VendorDeep Infra Inc.Meta
Hosted endpointhttps://api.deepinfra.com/v1/openaino (local only)
TransportsHTTPHTTP
AuthAPI keyNone
PricingPay per useFree
x402nono
LicenceProprietary service under the DeepInfra Terms of Service. The Python and Node SDKs and the docs repository are MITMuse 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 release2026-10-072026-10-15
Terms last updated2026-08-17
Privacy policy last updated2026-08-15no document linked
Customer content may train modelsnot found in the text
Terms restrict automated accessnot found in the text
Terms restrict benchmarkingyes
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Popularity21 stars, 1.2k npm/wk, 50 PyPI/wknone

Verdicts

DeepInfra

The model list, context sizes and per-token prices are readable without a key, and keys can carry an IP allowlist, a monthly spending cap and model-limited JWTs. Deprecated models get one week's notice and are then redirected to another model, there is no changelog or SLA, and an account needs a card or prepayment before any 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

DeepInfra

  1. Call GET https://api.deepinfra.com/v1/openai/models at start-up for ids, context sizes and prices. No key is needed
  2. Check the model field of each response. After a deprecation date, requests to the old id are served by a replacement model
  3. Ask the account owner for a scoped JWT limited to the models and spend the task needs, not the full API key
  4. Stay under 200 concurrent requests per model. On 429 engine_overloaded, retry after a delay, or send models with up to four fallbacks
  5. Never inspect a JWT with GET /v1/scoped-jwt?jwtoken=, which puts the token in the URL. Keep credentials in the Authorization header

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, DeepInfra or Muse Spark Open?

DeepInfra scores 63 (B) 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 DeepInfra and Muse Spark Open need an API key?

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

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

DeepInfra has a hosted endpoint at https://api.deepinfra.com/v1/openai. No hosted endpoint is listed for Muse Spark Open.

Other comparisons with DeepInfra or Muse Spark Open

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