Context Window

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MiniMax M3 (batch) vs Mistral Large 4

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 (batch)

Image inputTool calling

Context window

524K

524,288 tokens · ~393K words

Model page
Mistral

Model

Mistral Large 4

Image inputTool calling

Context window

524K

524,288 tokens · ~393K 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 M3 (batch)524K
Mistral Large 4524K

Same context window size for both models.

Token calculator →Memory savings →

MiniMax M3 (batch) and Mistral Large 4 have identical context windows (524K tokens). MiniMax M3 (batch) is 55% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use MiniMax M3 (batch). Input tokens are 55% 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 M3 (batch)Mistral Large 4
Context window524,288 tokens (524K)524,288 tokens (524K)
Max output tokens471,859 tokens (471K)N/A
Speed tierFastDeep
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
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 (batch) inMiniMax M3 (batch) outMistral Large 4 inMistral Large 4 out
Mistral——$0.680/M$2.09/M
Openrouter$0.300/M$1.20/M——

Frequently asked questions

Mistral Large 4 has a larger context window: 524K tokens vs 524K. 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