Kimi K2.5 vs Mistral Large 3 675B Instruct
Kimi K2.5 (2026) and Mistral Large 3 675B Instruct (2025) are agentic coding models from Moonshot AI and MistralAI. Kimi K2.5 ships a 256K-token context window, while Mistral Large 3 675B Instruct ships a 128K-token context window. On τ-bench, Kimi K2.5 leads by 4 pts. On pricing, Kimi K2.5 costs $0.38/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Kimi K2.5 is safer overall; choose Mistral Large 3 675B Instruct when provider fit matters.
Specs
| Released | 2026-03-15 | 2025-12-01 |
| Context window | 256K | 128K |
| Parameters | 1T (MoE, 384 experts) | 675B |
| Architecture | mixture of experts | decoder only |
| License | MIT | 1 |
| Knowledge cutoff | - | - |
Pricing and availability
| Kimi K2.5 | Mistral Large 3 675B Instruct | |
|---|---|---|
| Input price | $0.38/1M tokens | $0.5/1M tokens |
| Output price | $1.72/1M tokens | $1.5/1M tokens |
| Providers |
Capabilities
| Kimi K2.5 | Mistral Large 3 675B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Kimi K2.5 | Mistral Large 3 675B Instruct |
|---|---|---|
| τ-bench | 74.2 | 70.2 |
Deep dive
On shared benchmark coverage, τ-bench has Kimi K2.5 at 74.2 and Mistral Large 3 675B Instruct at 70.2, with Kimi K2.5 ahead by 4 points. The largest visible gap is 4 points on τ-bench, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: Kimi K2.5. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Kimi K2.5 lists $0.38/1M input and $1.72/1M output tokens, while Mistral Large 3 675B Instruct lists $0.5/1M input and $1.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.5 lower by about $0.02 per million blended tokens. Availability is 7 providers versus 3, so concentration risk also matters.
Choose Kimi K2.5 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Mistral Large 3 675B Instruct when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Kimi K2.5 or Mistral Large 3 675B Instruct?
Kimi K2.5 supports 256K tokens, while Mistral Large 3 675B Instruct supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Kimi K2.5 or Mistral Large 3 675B Instruct?
Kimi K2.5 is cheaper on tracked token pricing. Kimi K2.5 costs $0.38/1M input and $1.72/1M output tokens. Mistral Large 3 675B Instruct costs $0.5/1M input and $1.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2.5 or Mistral Large 3 675B Instruct open source?
Kimi K2.5 is listed under MIT. Mistral Large 3 675B Instruct is listed under 1. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for function calling, Kimi K2.5 or Mistral Large 3 675B Instruct?
Kimi K2.5 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, Kimi K2.5 or Mistral Large 3 675B Instruct?
Both Kimi K2.5 and Mistral Large 3 675B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Kimi K2.5 and Mistral Large 3 675B Instruct?
Kimi K2.5 is available on Fireworks AI, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Mistral Large 3 675B Instruct is available on AWS Bedrock, NVIDIA NIM, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.