Kimi K2.5 vs Qwen3.6-35B-A3B
Kimi K2.5 (2026) and Qwen3.6-35B-A3B (2026) are agentic coding models from Moonshot AI and Alibaba. Kimi K2.5 ships a 256K-token context window, while Qwen3.6-35B-A3B ships a 262K-token context window. On MMLU PRO, Kimi K2.5 leads by 1.9 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.6-35B-A3B is safer overall; choose Kimi K2.5 when coding workflow support matters.
Specs
| Released | 2026-03-15 | 2026-04-16 |
| Context window | 256K | 262K |
| Parameters | 1T (MoE, 384 experts) | 35 |
| Architecture | mixture of experts | moe |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Kimi K2.5 | Qwen3.6-35B-A3B | |
|---|---|---|
| Input price | $0.38/1M tokens | - |
| Output price | $1.72/1M tokens | - |
| Providers | - |
Capabilities
| Kimi K2.5 | Qwen3.6-35B-A3B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-35B-A3B |
|---|---|---|
| MMLU PRO | 87.1 | 85.2 |
| Google-Proof Q&A | 87.9 | 86.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Kimi K2.5 at 87.1 and Qwen3.6-35B-A3B at 85.2, with Kimi K2.5 ahead by 1.9 points; Google-Proof Q&A has Kimi K2.5 at 87.9 and Qwen3.6-35B-A3B at 86, with Kimi K2.5 ahead by 1.9 points. The largest visible gap is 1.9 points on Google-Proof Q&A, 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 multimodal input: Qwen3.6-35B-A3B, tool use: Qwen3.6-35B-A3B, and structured outputs: Kimi K2.5. Both models share function calling, 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.
Pricing coverage is uneven: Kimi K2.5 has $0.38/1M input tokens and Qwen3.6-35B-A3B has no token price sourced yet. Provider availability is 7 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Kimi K2.5 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support and larger context windows 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 Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B supports 262K tokens, while Kimi K2.5 supports 256K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is Kimi K2.5 or Qwen3.6-35B-A3B open source?
Kimi K2.5 is listed under MIT. Qwen3.6-35B-A3B is listed under Apache 2.0. 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 multimodal input, Kimi K2.5 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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.
Which is better for function calling, Kimi K2.5 or Qwen3.6-35B-A3B?
Both Kimi K2.5 and Qwen3.6-35B-A3B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for tool use, Kimi K2.5 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the clearer documented tool use signal in this comparison. If tool use 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 Qwen3.6-35B-A3B?
Kimi K2.5 is available on Fireworks AI, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Qwen3.6-35B-A3B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.