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Codestral 2405 vs Qwen2 5 7b
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.
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.
Qwen2 5 7b has about 1× the context window of the other in this pair.
Qwen2 5 7b has 2% more context capacity (32K vs 32K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen2 5 7b. Its 32K context fits entire documents without chunking (vs 32K).
Long output (reports, code files)
Use Qwen2 5 7b. 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.
| Spec | Codestral 2405 | Qwen2 5 7b |
|---|---|---|
| Context window | 32,000 tokens (32K) | 32,768 tokens (32K) |
| Max output tokens | 8,191 tokens (8K) | 32,768 tokens (32K) |
| Speed tier | Balanced | Fast |
| Vision | No | No |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | N/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.
| Provider | Codestral 2405 in | Codestral 2405 out | Qwen2 5 7b in | Qwen2 5 7b out |
|---|---|---|---|---|
| Deepinfra | — | — | $0.040/M | $0.100/M |
| Google Vertex | $0.200/M | $0.600/M | — | — |
| Mistral | — | — | — | — |
| Novita | — | — | $0.070/M | $0.070/M |
Frequently asked questions
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Example: a multi-turn chat session
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