Context Window

Compare

Mistral Medium Latest vs Mistral Nemo

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 Medium Latest

Image inputTool calling

Context window

131K

131,072 tokens · ~98K words

Model page
Mistral

Model

Mistral Nemo

Tool 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.

Mistral Medium Latest131K
Mistral Nemo131K

Same context window size for both models.

Token calculator →Memory savings →

Mistral Medium Latest and Mistral Nemo have identical context windows (131K tokens). Mistral Nemo is 62% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Mistral Nemo. Input tokens are 62% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Mistral Medium Latest. Its 131K max output lets you generate complete artifacts in one request.

Full specs

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

SpecMistral Medium LatestMistral Nemo
Context window131,072 tokens (131K)131,072 tokens (131K)
Max output tokens131,072 tokens (131K)4,096 tokens (4K)
Speed tierBalancedBalanced
VisionYesNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJul 2024

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 Medium Latest inMistral Medium Latest outMistral Nemo inMistral Nemo out
Azure——$0.150/M$0.150/M
Mistral$0.400/M$2.00/M——
Novita——$0.040/M$0.170/M

Frequently asked questions

Mistral Nemo 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.

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