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Nano Banana 2 (Gemini 3.1 Flash Image) vs Mistral Medium 3.1

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.

Google

Model

Nano Banana 2 (Gemini 3.1 Flash Image)

Image input

Context window

131K

131,072 tokens · ~98K words

Model page
Mistral

Model

Mistral Medium 3.1

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.

Nano Banana 2 (Gemini 3.1 Flash Image)131K
Mistral Medium 3.1131K

Same context window size for both models.

Nano Banana 2 (Gemini 3.1 Flash Image) and Mistral Medium 3.1 have identical context windows (131K tokens).

Full specs

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

SpecNano Banana 2 (Gemini 3.1 Flash Image)Mistral Medium 3.1
Context window131,072 tokens (131K)131,072 tokens (131K)
Max output tokens65,536 tokens (65K)N/A
Speed tierFastBalanced
VisionYesYes
Function callingNoYes
Extended thinkingYesNo
Prompt cachingNoYes
Batch APINoNo
Release dateJun 2026Aug 2025

Frequently asked questions

Mistral Medium 3.1 has a larger context window: 131K 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