Context Window

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Mistral Pixtral Large 2502 vs Qwen VL Plus

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 Pixtral Large 2502

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen VL Plus

Image input

Context window

8K

8,192 tokens · ~6K 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 Pixtral Large 2502128K
Qwen VL Plus8K

Mistral Pixtral Large 2502 has about 15.6× the context window of the other in this pair.

Token calculator →Memory savings →

Mistral Pixtral Large 2502 has 1462% more context capacity (128K vs 8K tokens). Qwen VL Plus is 89% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Mistral Pixtral Large 2502. Its 128K context fits entire documents without chunking (vs 8K).

  • RAG / high-volume retrieval

    Use Qwen VL Plus. Input tokens are 89% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Mistral Pixtral Large 2502. Its 4K 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 Pixtral Large 2502Qwen VL Plus
Context window128,000 tokens (128K)8,192 tokens (8K)
Max output tokens4,096 tokens (4K)2,048 tokens (2K)
Speed tierDeepBalanced
VisionNoYes
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoYes
Batch APINoNo
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 Pixtral Large 2502 inMistral Pixtral Large 2502 outQwen VL Plus inQwen VL Plus out
Aws Bedrock$2.00/M$6.00/M——
Openrouter——$0.210/M$0.630/M

Frequently asked questions

Mistral Pixtral Large 2502 has a larger context window: 128K tokens vs 8K. 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.
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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