Context Window

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GPT-4o-mini Search Preview vs Mistral Pixtral Large 2502

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.

Openai

Model

GPT-4o-mini Search Preview

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Mistral

Model

Mistral Pixtral Large 2502

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.

GPT-4o-mini Search Preview128K
Mistral Pixtral Large 2502128K

Same context window size for both models.

Token calculator →Memory savings →

GPT-4o-mini Search Preview and Mistral Pixtral Large 2502 have identical context windows (128K tokens). GPT-4o-mini Search Preview is 92% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use GPT-4o-mini Search Preview. Input tokens are 92% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use GPT-4o-mini Search Preview. Its 16K 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.

SpecGPT-4o-mini Search PreviewMistral Pixtral Large 2502
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)4,096 tokens (4K)
Speed tierFastDeep
VisionYesNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingYesNo
Batch APIYesNo
Release dateMar 2025N/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.

ProviderGPT-4o-mini Search Preview inGPT-4o-mini Search Preview outMistral Pixtral Large 2502 inMistral Pixtral Large 2502 out
Aws Bedrock——$2.00/M$6.00/M
Openai$0.150/M$0.600/M——

Frequently asked questions

Mistral Pixtral Large 2502 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.

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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.

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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