Context Window

Compare

Minimax Minimax M2 vs Mistral Ministral 3 3b

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 Minimax M2

Context window

128K

128,000 tokens · ~96K words

Model page
Mistral

Model

Mistral Ministral 3 3b

Tool calling

Context window

128K

128,000 tokens · ~96K 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 Minimax M2128K
Mistral Ministral 3 3b128K

Same context window size for both models.

Token calculator →Memory savings →

Minimax Minimax M2 and Mistral Ministral 3 3b have identical context windows (128K tokens). Mistral Ministral 3 3b is 66% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Mistral Ministral 3 3b. Input tokens are 66% 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 Minimax M2Mistral Ministral 3 3b
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens8,192 tokens (8K)8,192 tokens (8K)
Speed tierFastFast
VisionNoNo
Function callingNoYes
Extended thinkingNoNo
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.

ProviderMinimax Minimax M2 inMinimax Minimax M2 outMistral Ministral 3 3b inMistral Ministral 3 3b out
Aws Bedrock$0.300/M$1.20/M$0.100/M$0.100/M

Frequently asked questions

Mistral Ministral 3 3b has a larger context window: 128K tokens vs 128K. 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