Context Window

Compare

Mistral Large Latest vs o3 Mini High

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 Large Latest

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page
Openai

Model

o3 Mini High

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.

Mistral Large Latest32K
o3 Mini High128K

o3 Mini High has about 4× the context window of the other in this pair.

Token calculator →Memory savings →

o3 Mini High has 300% more context capacity (128K vs 32K tokens). Mistral Large Latest is 54% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use o3 Mini High. Its 128K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Mistral Large Latest. Input tokens are 54% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMistral Large Latesto3 Mini High
Context window32,000 tokens (32K)128,000 tokens (128K)
Max output tokensN/A65,536 tokens (65K)
Speed tierDeepFast
VisionNoNo
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoYes
Batch APINoYes
Release dateN/AFeb 2025

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 Large Latest inMistral Large Latest outo3 Mini High ino3 Mini High out
Azure$8.00/M$24.00/M——
Google Vertex$2.00/M$6.00/M——
Mistral$0.500/M$1.50/M——
Openrouter——$1.10/M$4.40/M

Frequently asked questions

o3 Mini High has a larger context window: 128K tokens vs 32K. 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