Mistral Large 3 vs Kimi K2.7 Code
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Mistral Large 3 | Kimi K2.7 Code |
|---|---|---|
| Provider | Mistral | Moonshot AI |
| Input Price (1M) | $0.50 | $0.95 |
| Output Price (1M) | $1.50 | $4.00 |
| Context Window | 262,000 | 262,144 |
Verdict
Mistral Large 3 costs $0.50 per 1M input tokens and $1.50 per 1M output tokens. Kimi K2.7 Code costs $0.95 per 1M input tokens and $4.00 per 1M output tokens. Mistral Large 3 is 47% cheaper on input tokens than Kimi K2.7 Code. For output tokens, Mistral Large 3 is the more affordable option at $1.50/1M vs $4.00.
On context window, Kimi K2.7 Code supports 262,144 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Mistral Large 3
- ✓ You need the lowest input token cost ($ 0.50/1M)
- ✓ Your workload is output-heavy — Mistral Large 3 generates text cheaper
- ✓ You are already integrated with Mistral
When to choose Kimi K2.7 Code
- ✓ 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 Mistral Large 3 cheaper than Kimi K2.7 Code? ▼
Mistral Large 3 is cheaper on input tokens at $0.50/1M vs $0.95/1M for Kimi K2.7 Code — a 47% saving.
What is the context window of Mistral Large 3 vs Kimi K2.7 Code? ▼
Mistral Large 3 has a 262,000-token context window. Kimi K2.7 Code has a 262,144-token context window. Kimi K2.7 Code supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Mistral Large 3 or Kimi K2.7 Code? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Mistral Large 3 is the cheaper option. For maximum context length, Kimi K2.7 Code supports 262,144 tokens. Use the comparison table above to find the right fit for your workload.