Mistral Medium 3 vs Kimi K3
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Mistral Medium 3 | Kimi K3 |
|---|---|---|
| Provider | Mistral | Moonshot AI |
| Input Price (1M) | $0.40 | $3.00 |
| Output Price (1M) | $2.00 | $15.00 |
| Context Window | 131,000 | 1,000,000 |
Verdict
Mistral Medium 3 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens. Kimi K3 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens. Mistral Medium 3 is 87% cheaper on input tokens than Kimi K3. For output tokens, Mistral Medium 3 is the more affordable option at $2.00/1M vs $15.00.
On context window, Kimi K3 supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Mistral Medium 3
- ✓ You need the lowest input token cost ($ 0.40/1M)
- ✓ Your workload is output-heavy — Mistral Medium 3 generates text cheaper
- ✓ You are already integrated with Mistral
When to choose Kimi K3
- ✓ You need a larger context window (1,000,000 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 Medium 3 cheaper than Kimi K3? ▼
Mistral Medium 3 is cheaper on input tokens at $0.40/1M vs $3.00/1M for Kimi K3 — a 87% saving.
What is the context window of Mistral Medium 3 vs Kimi K3? ▼
Mistral Medium 3 has a 131,000-token context window. Kimi K3 has a 1,000,000-token context window. Kimi K3 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Mistral Medium 3 or Kimi K3? ▼
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 K3 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.