Codestral vs Kimi K2.5
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Codestral | Kimi K2.5 |
|---|---|---|
| Provider | Mistral | Moonshot AI |
| Input Price (1M) | $0.30 | $0.60 |
| Output Price (1M) | $0.90 | $3.00 |
| Context Window | 256,000 | 262,144 |
Verdict
Codestral costs $0.30 per 1M input tokens and $0.90 per 1M output tokens. Kimi K2.5 costs $0.60 per 1M input tokens and $3.00 per 1M output tokens. Codestral is 50% cheaper on input tokens than Kimi K2.5. For output tokens, Codestral is the more affordable option at $0.90/1M vs $3.00.
On context window, Kimi K2.5 supports 262,144 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Codestral
- ✓ You need the lowest input token cost ($ 0.30/1M)
- ✓ Your workload is output-heavy — Codestral generates text cheaper
- ✓ You are already integrated with Mistral
When to choose Kimi K2.5
- ✓ You need a larger context window (262,144 tokens)
- ✓ You are already integrated with Moonshot AI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Codestral cheaper than Kimi K2.5? ▼
Codestral is cheaper on input tokens at $0.30/1M vs $0.60/1M for Kimi K2.5 — a 50% saving.
What is the context window of Codestral vs Kimi K2.5? ▼
Codestral has a 256,000-token context window. Kimi K2.5 has a 262,144-token context window. Kimi K2.5 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Codestral or Kimi K2.5? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Codestral is the cheaper option. For maximum context length, Kimi K2.5 supports 262,144 tokens. Use the comparison table above to find the right fit for your workload.