Kimi K2.5 vs Mistral Large 2
Kimi K2.5 (2026) and Mistral Large 2 (2025) are agentic coding models from Moonshot AI and MistralAI. Kimi K2.5 ships a 256K-token context window, while Mistral Large 2 ships a 128K-token context window. On MMLU PRO, Kimi K2.5 leads by 17.4 pts. On pricing, Kimi K2.5 costs $0.38/1M input tokens versus $0.48/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Kimi K2.5 is safer overall; choose Mistral Large 2 when vision-heavy evaluation matters.
Specs
| Released | 2026-03-15 | 2025-11-25 |
| Context window | 256K | 128K |
| Parameters | 1T (MoE, 384 experts) | 123B |
| Architecture | mixture of experts | decoder only |
| License | MIT | True |
| Knowledge cutoff | - | 2025-07 |
Pricing and availability
| Kimi K2.5 | Mistral Large 2 | |
|---|---|---|
| Input price | $0.38/1M tokens | $0.48/1M tokens |
| Output price | $1.72/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Kimi K2.5 | Mistral Large 2 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Kimi K2.5 | Mistral Large 2 |
|---|---|---|
| MMLU PRO | 87.1 | 69.7 |
| BFCL | 68.3 | 38.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has Kimi K2.5 at 87.1 and Mistral Large 2 at 69.7, with Kimi K2.5 ahead by 17.4 points; BFCL has Kimi K2.5 at 68.3 and Mistral Large 2 at 38.4, with Kimi K2.5 ahead by 29.9 points. The largest visible gap is 29.9 points on BFCL, 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 vision: Mistral Large 2, multimodal input: Mistral Large 2, and tool use: Mistral Large 2. Both models share function calling and 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 2 lists $0.48/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.5 lower by about $0.27 per million blended tokens. Availability is 7 providers versus 4, 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 2 when vision-heavy evaluation 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 2?
Kimi K2.5 supports 256K tokens, while Mistral Large 2 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 2?
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 2 costs $0.48/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2.5 or Mistral Large 2 open source?
Kimi K2.5 is listed under MIT. Mistral Large 2 is listed under True. 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 vision, Kimi K2.5 or Mistral Large 2?
Mistral Large 2 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Kimi K2.5 or Mistral Large 2?
Mistral Large 2 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Kimi K2.5 and Mistral Large 2?
Kimi K2.5 is available on Fireworks AI, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, 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.