Context Window

Compare

Magistral Medium Latest vs Qwen2 1 5b

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

Magistral Medium Latest

Tool calling

Context window

40K

40,000 tokens · ~30K words

Model page
Alibaba

Model

Qwen2 1 5b

Context window

33K

32,768 tokens · ~25K 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.

Magistral Medium Latest40K
Qwen2 1 5b33K

Magistral Medium Latest has about 1.2× the context window of the other in this pair.

Token calculator →Memory savings →

Magistral Medium Latest has 22% more context capacity (40K vs 32K tokens). Qwen2 1 5b is 98% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Magistral Medium Latest. Its 40K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Qwen2 1 5b. Input tokens are 98% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMagistral Medium LatestQwen2 1 5b
Context window40,000 tokens (40K)32,768 tokens (32K)
Max output tokens40,000 tokens (40K)N/A
Speed tierBalancedBalanced
VisionNoNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateN/AN/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.

ProviderMagistral Medium Latest inMagistral Medium Latest outQwen2 1 5b inQwen2 1 5b out
Mistral$1.50/M$7.50/M——
Together Ai——$0.020/M$0.020/M

Frequently asked questions

Magistral Medium Latest has a larger context window: 40K 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