Context Window

Compare

Open Mistral 7b 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

Open Mistral 7b

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.

Open Mistral 7b32K
Qwen2.5 72B Instruct32K

Same context window size for both models.

Token calculator →Memory savings →

Open Mistral 7b and Qwen2.5 72B Instruct have identical context windows (32K tokens). Open Mistral 7b is 34% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Open Mistral 7b. Input tokens are 34% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Qwen2.5 72B Instruct. Its 8K 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.

SpecOpen Mistral 7bQwen2.5 72B Instruct
Context window32,000 tokens (32K)32,000 tokens (32K)
Max output tokens8,191 tokens (8K)8,192 tokens (8K)
Speed tierFastDeep
VisionNoNo
Function callingNoYes
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.

ProviderOpen Mistral 7b inOpen Mistral 7b outQwen2.5 72B Instruct inQwen2.5 72B Instruct out
Mistral$0.250/M$0.250/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.

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