Context Window

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MiniMax M3 vs Mistral Medium Latest

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.

Minimax

Model

MiniMax M3

Image inputTool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Mistral

Model

Mistral Medium Latest

Image inputTool calling

Context window

131K

131,072 tokens · ~98K 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.

MiniMax M31.0M
Mistral Medium Latest131K

MiniMax M3 has about 8× the context window of the other in this pair.

Token calculator →Memory savings →

MiniMax M3 has 700% more context capacity (1048K vs 131K tokens). MiniMax M3 is 80% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use MiniMax M3. Its 1048K context fits entire documents without chunking (vs 131K).

  • RAG / high-volume retrieval

    Use MiniMax M3. Input tokens are 80% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMiniMax M3Mistral Medium Latest
Context window1,048,576 tokens (1048K)131,072 tokens (131K)
Max output tokens131,072 tokens (131K)131,072 tokens (131K)
Speed tierFastBalanced
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesNo
Batch APINoNo
Release dateMay 2026N/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.

ProviderMiniMax M3 inMiniMax M3 outMistral Medium Latest inMistral Medium Latest out
Fireworks$0.300/M$1.20/M——
Minimax$0.300/M$1.20/M——
Mistral——$1.50/M$7.50/M

Frequently asked questions

MiniMax M3 has a larger context window: 1048K 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.

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