Kimi K2.5 vs Mistral Medium 3
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Kimi K2.5 | Mistral Medium 3 |
|---|---|---|
| Provider | Moonshot AI | Mistral |
| Input Price (1M) | $0.60 | $0.40 |
| Output Price (1M) | $3.00 | $2.00 |
| Context Window | 262,144 | 131,000 |
Verdict
Kimi K2.5 costs $0.60 per 1M input tokens and $3.00 per 1M output tokens. Mistral Medium 3 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens. Mistral Medium 3 is 33% cheaper on input tokens than Kimi K2.5. For output tokens, Mistral Medium 3 is the more affordable option at $2.00/1M vs $3.00.
On context window, Kimi K2.5 supports 262,144 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Kimi K2.5
- ✓ You need a larger context window (262,144 tokens)
- ✓ You are already integrated with Moonshot AI
When to choose Mistral Medium 3
- ✓ You need the lowest input token cost ($ 0.40/1M)
- ✓ Your workload is output-heavy — Mistral Medium 3 generates text cheaper
- ✓ You are already integrated with Mistral
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 Kimi K2.5 cheaper than Mistral Medium 3? ▼
Mistral Medium 3 is cheaper on input tokens at $0.40/1M vs $0.60/1M for Kimi K2.5 — a 33% saving.
What is the context window of Kimi K2.5 vs Mistral Medium 3? ▼
Kimi K2.5 has a 262,144-token context window. Mistral Medium 3 has a 131,000-token context window. Kimi K2.5 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Kimi K2.5 or Mistral Medium 3? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Mistral Medium 3 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.