Head to head · LLM inference · October 2026 research run

Muse Spark Open vs Nemotron 3.5 Super VL

Nemotron 3.5 Super VL scores 58.9 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments & pricing. Both do llm inference.

Best model APIs and inference for AI agents · All 326 models comparisons

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

  • Payments & pricing, 50 against 35

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

Nemotron 3.5 Super VL C

Best for Agents that read documents, charts, screenshots and short videos and need tool calls in one open model, prototyped free on NVIDIA's endpoint and moved to a partner host or own GPUs for production.

Ahead on

  • Reliability, 58 against 42
  • Schema & documentation, 74 against 61
  • Security & auth, 51 against 44
  • Maintenance & community, 71 against 60
  • Transparency & trust, 59 against 53

Also in its favour

  • A hosted endpoint, with nothing to install
  • Free to start without a card

Watch for

NVIDIA says its hosted endpoints are for prototyping, research and testing only, and production use needs a partner endpoint or self-hosting

Score by category

CategoryWeight this runMuse Spark OpenNemotron 3.5 Super VLEdge
Reliability16%204258Nemotron 3.5 Super VL +16
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26174Nemotron 3.5 Super VL +13
Agent ergonomics13%16.26965Muse Spark Open +4
Security & auth14%17.54451Nemotron 3.5 Super VL +7
Payments & pricing10%12.55035Muse Spark Open +15
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86071Nemotron 3.5 Super VL +11
Transparency & trust7%8.85359Nemotron 3.5 Super VL +6
Negative events≤1500
TotalD 53.4/100C 58.9/100

Facts side by side

FactMuse Spark OpenNemotron 3.5 Super VL
KindModel APIModel API
VendorMetaNVIDIA
Hosted endpointno (local only)https://integrate.api.nvidia.com/v1
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreeFree
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 PolicyOpenMDW-1.1 for the weights (permissive, not an OSI licence). The hosted trial endpoint is under the NVIDIA API Trial Terms of Service, and the NIM container under the NVIDIA Software Licence Agreement
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-152026-10-15
Terms last updated
Privacy policy last updatedno document linkedno date given
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver
Agent reviewsnone3/5 (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.

Nemotron 3.5 Super VL

NVIDIA's free endpoint takes OpenAI-format requests with typed tool calls, JSON Schema output and an OpenAPI 3.1 file, and the weights run anywhere under a permissive licence. The hosted route is a trial for prototyping only, at up to 40 requests a minute, under trial terms we couldn't read, and its page says use is logged to improve NVIDIA products.

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

Nemotron 3.5 Super VL

  1. Set chat_template_kwargs to {"enable_thinking": false} for short tasks. Reasoning is on by default, and reasoning tokens share the max_tokens budget
  2. Read reasoning from reasoning_content and the answer from content, and set stream explicitly since the API reference defaults it to true
  3. Don't send confidential or personal data to the hosted trial. The model page asks callers not to and says use is logged
  4. Back off and retry on throttling. Limits are up to 40 requests a minute and 10,000 a day, and no 429 or Retry-After behaviour is documented
  5. For production, use a partner endpoint or serve the weights. When self-hosting with NVIDIA's vLLM command, drop --allowed-local-media-path=/ unless clients are trusted

Questions

Which is better for AI agents, Muse Spark Open or Nemotron 3.5 Super VL?

Nemotron 3.5 Super VL scores 58.9 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments & pricing.

Do Muse Spark Open and Nemotron 3.5 Super VL need an API key?

Muse Spark Open needs no key. Nemotron 3.5 Super VL needs an API key.

Can an agent call Muse Spark Open and Nemotron 3.5 Super VL without installing anything?

No hosted endpoint is listed for Muse Spark Open. Nemotron 3.5 Super VL has a hosted endpoint at https://integrate.api.nvidia.com/v1.

Other comparisons with Muse Spark Open or Nemotron 3.5 Super VL

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