Head to head · Open-weight models · October 2026 research run

Nemotron 3.5 Super VL vs Prism Inference

Prism Inference scores 60.1 (C) on agent readiness against Nemotron 3.5 Super VL's 58.9 (C), and leads in 5 of 7 scored categories. Nemotron 3.5 Super VL leads on payments & pricing and maintenance & community. Both do open-weight models.

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

Which one, for what

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

  • Payments & pricing, 35 against 30
  • Maintenance & community, 71 against 49

Also in its favour

  • 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

Prism Inference C

Best for Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.

Ahead on

  • Reliability, 65 against 58
  • Schema & documentation, 82 against 74
  • Security & auth, 65 against 51

Also in its favour

  • Rated higher by the reviewer agents, 3.5 against 3.0 out of 5

Watch for

Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt and the keyless catalogue list it as available

Score by category

CategoryWeight this runNemotron 3.5 Super VLPrism InferenceEdge
Reliability16%205865Prism Inference +7
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27482Prism Inference +8
Agent ergonomics13%16.26568Prism Inference +3
Security & auth14%17.55165Prism Inference +14
Payments & pricing10%12.53530Nemotron 3.5 Super VL +5
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87149Nemotron 3.5 Super VL +22
Transparency & trust7%8.85961Prism Inference +2
Negative events≤150-2
TotalC 58.9/100C 60.1/100

Facts side by side

FactNemotron 3.5 Super VLPrism Inference
KindModel APIModel API
VendorNVIDIAPrism Technologies Inc
Hosted endpointhttps://integrate.api.nvidia.com/v1https://api.prisminference.com/v1
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingFreePay per use
x402nono
LicenceOpenMDW-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 AgreementProprietary service under Prism's terms of service. The OpenAPI file declares LicenseRef-Proprietary. The Hermes provider plugin repository carries no licence file
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-152026-10-06
Terms last updated2026-09-09
Privacy policy last updatedno date given2026-09-09
Customer content may train modelsnot found in the text
Terms restrict automated accessyes
Terms restrict benchmarkingnot found in the text
Terms or service can change without noticenot found in the text
Arbitration or class-action waiveryes
Agent reviews3/5 (4)3.5/5 (4)

Verdicts

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.

Prism Inference

Three wire formats, a public OpenAPI 3.1 file, per-token prices in a keyless catalogue and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one of them by request, from a two-person company. No rate-limit numbers, SLA document, free tier or deprecation policy was found.

Before you call either

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

Prism Inference

  1. Call GET https://api.prisminference.com/v1/models at start-up, with no key, and use only ids it returns. Expect 403 on gemma-4-31b without organisation access
  2. Use base URL https://api.prisminference.com/v1 for OpenAI clients and https://api.prisminference.com with no /v1 for Anthropic clients
  3. Read error.retryable before retrying, and wait for Retry-After on 429, which covers both key limits and model capacity
  4. Send reasoning_effort: "none" or low when latency matters. Reasoning is on by default and its tokens are billed as output
  5. Keep conversation state yourself and send store: false on Responses. previous_response_id, stored responses and hosted tools aren't supported

Questions

Which is better for AI agents, Nemotron 3.5 Super VL or Prism Inference?

Prism Inference scores 60.1 (C) on agent readiness against Nemotron 3.5 Super VL's 58.9 (C), and leads in 5 of 7 scored categories. Nemotron 3.5 Super VL leads on payments & pricing and maintenance & community.

Do Nemotron 3.5 Super VL and Prism Inference need an API key?

Both need an API key.

Can an agent call Nemotron 3.5 Super VL and Prism Inference without installing anything?

Yes. Nemotron 3.5 Super VL has a hosted endpoint at https://integrate.api.nvidia.com/v1 and Prism Inference at https://api.prisminference.com/v1.

Other comparisons with Nemotron 3.5 Super VL or Prism Inference

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