Compare

Mistral Small 3 2 2506 vs Nvidia Nemotron 3 5 Lightning

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Mistral

Model

Mistral Small 3 2 2506

Image inputTool calling

Context window

131K

131,072 tokens · ~98K words

Model page
Nvidia

Model

Nvidia Nemotron 3 5 Lightning

Tool calling

Context window

262K

262,144 tokens · ~197K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Mistral Small 3 2 2506131K
Nvidia Nemotron 3 5 Lightning262K

Nvidia Nemotron 3 5 Lightning has about 2× the context window of the other in this pair.

Nvidia Nemotron 3 5 Lightning has 100% more context capacity (262K vs 131K tokens). Nvidia Nemotron 3 5 Lightning is 16% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Nvidia Nemotron 3 5 Lightning. Its 262K context fits entire documents without chunking (vs 131K).

  • RAG / high-volume retrieval

    Use Nvidia Nemotron 3 5 Lightning. Input tokens are 16% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecMistral Small 3 2 2506Nvidia Nemotron 3 5 Lightning
Context window131,072 tokens (131K)262,144 tokens (262K)
Max output tokens131,072 tokens (131K)N/A
Speed tierBalancedBalanced
VisionYesNo
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderMistral Small 3 2 2506 inMistral Small 3 2 2506 outNvidia Nemotron 3 5 Lightning inNvidia Nemotron 3 5 Lightning out
Deepinfra$0.050/M$0.200/M
Mistral$0.060/M$0.180/M

Frequently asked questions

Nvidia Nemotron 3 5 Lightning has a larger context window: 262K tokens vs 131K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model