Context Window

Compare

Mistral Large Latest vs Mistral Small 3

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 Large Latest

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page
Mistral

Model

Mistral Small 3

Tool calling

Context window

33K

32,768 tokens · ~25K 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 Large Latest32K
Mistral Small 333K

Mistral Small 3 has about 1× the context window of the other in this pair.

Token calculator →Memory savings →

Mistral Small 3 has 2% more context capacity (32K vs 32K tokens). Mistral Small 3 is 90% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Mistral Small 3. Its 32K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Mistral Small 3. Input tokens are 90% 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 Large LatestMistral Small 3
Context window32,000 tokens (32K)32,768 tokens (32K)
Max output tokensN/A32,768 tokens (32K)
Speed tierDeepBalanced
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJan 2025

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 Large Latest inMistral Large Latest outMistral Small 3 inMistral Small 3 out
Azure$8.00/M$24.00/M——
Deepinfra——$0.050/M$0.080/M
Fireworks——$0.900/M$0.900/M
Google Vertex$2.00/M$6.00/M——
Mistral$0.500/M$1.50/M——
Together Ai————

Frequently asked questions

Mistral Small 3 has a larger context window: 32K tokens vs 32K. 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.

Calculate your savingsLearn about Mem0

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