Context Window

Compare

Mistral Small 3 1 24b Instruct 2503 vs Qwen2.5 72B Instruct

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 Small 3 1 24b Instruct 2503

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page
Alibaba

Model

Qwen2.5 72B Instruct

Tool calling

Context window

32K

32,000 tokens · ~24K 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 Small 3 1 24b Instruct 250332K
Qwen2.5 72B Instruct32K

Same context window size for both models.

Token calculator →Memory savings →

Mistral Small 3 1 24b Instruct 2503 and Qwen2.5 72B Instruct have identical context windows (32K tokens). Mistral Small 3 1 24b Instruct 2503 is 73% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Mistral Small 3 1 24b Instruct 2503. Input tokens are 73% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Mistral Small 3 1 24b Instruct 2503. Its 32K 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 Small 3 1 24b Instruct 2503Qwen2.5 72B Instruct
Context window32,000 tokens (32K)32,000 tokens (32K)
Max output tokens32,000 tokens (32K)8,192 tokens (8K)
Speed tierBalancedDeep
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/ASep 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 Small 3 1 24b Instruct 2503 inMistral Small 3 1 24b Instruct 2503 outQwen2.5 72B Instruct inQwen2.5 72B Instruct out
Ibm Watsonx$0.100/M$0.300/M——
Novita——$0.380/M$0.400/M

Frequently asked questions

Qwen2.5 72B Instruct has a larger context window: 32K 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.

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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