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Model comparison

Mistral Medium 3.5 vs NVIDIA Nemotron 3.5 Lightning

Compare Mistral Medium 3.5 and NVIDIA Nemotron 3.5 Lightning using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.

Facts checked September 4, 2026

Estimate your cost

Set your usage. Your estimate updates as you type.

Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.

One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.

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How this estimate works

Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.

Estimate your cost
ModelEstimated total (USD)
Mistral Medium 3.5Mistral AINo reviewed rate
NVIDIA Nemotron 3.5 LightningNVIDIANo reviewed rate

Quick take

Mistral Medium 3.5

Mistral's open-weight frontier model for demanding multimodal, coding, reasoning, and agent workflows, with a 256K context window.

Best for

  • Complex coding and agent workflows
  • Multimodal document and image reasoning
  • Organizations choosing between hosted and controlled deployment

Watch out for

The headline token price applies to Mistral's standard hosted endpoint. Regional inference costs more, and self-hosting shifts the bill to GPUs, operations, and support.

NVIDIA Nemotron 3.5 Lightning

NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.

Best for

  • High-volume agent sub-tasks
  • Efficient self-hosted reasoning
  • Long-context RAG and instruction workflows

Watch out for

The current release is labeled preview. Validate the exact precision, language, tool template, provider route, and long-context memory needs before standardizing a production fleet.

Compare the published facts

Mistral Medium 3.5 vs NVIDIA Nemotron 3.5 Lightning

Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.

Text & reasoningMistral Medium 3.5NVIDIA Nemotron 3.5 Lightning
Context windowMaximum combined prompt and working context documented by the provider.256K tokens combinedUp to 1M tokens
Maximum outputProvider-published response limit, where available.Not separately publishedNot separately published
Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff.Not publishedPretraining through Sep 2025; post-training through May 2026
Input priceCurrent standard list price per million input tokens unless noted.$1.50 / 1MFree prototype or deployment cost
Output priceCurrent standard list price per million output tokens unless noted.$7.50 / 1MFree prototype or deployment cost
InputsMedia types accepted by the listed model endpoint.Text, imageText
Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list.Functions, agents, built-in tools, structured and predicted outputsAgentic tools and long-running workflows

How to choose

Compare the job, not the hype.

Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.

Mistral Medium 3.5

Mistral's commercial terms exclude model training by default except when a customer opts in or uses designated Labs or preview models. Standard API input and output retention is generally 30 rolling days for abuse monitoring unless zero data retention is enabled.

NVIDIA Nemotron 3.5 Lightning

Self-hosted weights keep request data under the operator's controls. NVIDIA API trials, OpenRouter, and cloud partners each apply separate logging, retention, and training-use policies.

Frequently asked questions

Mistral Medium 3.5 vs NVIDIA Nemotron 3.5 Lightning FAQ

What is the main difference between Mistral Medium 3.5 and NVIDIA Nemotron 3.5 Lightning?

Mistral Medium 3.5: Mistral's open-weight frontier model for demanding multimodal, coding, reasoning, and agent workflows, with a 256K context window. NVIDIA Nemotron 3.5 Lightning: NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.

Should I choose Mistral Medium 3.5 or NVIDIA Nemotron 3.5 Lightning?

Consider Mistral Medium 3.5 when your priority is Complex coding and agent workflows. Consider NVIDIA Nemotron 3.5 Lightning when your priority is High-volume agent sub-tasks. Test both with your own data and provider route before committing.

Is this Mistral Medium 3.5 vs NVIDIA Nemotron 3.5 Lightning comparison based on Cody benchmarks?

No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.