Kimi K2.5 vs Qwen3.5-27B
Kimi K2.5 (2026) and Qwen3.5-27B (2026) are agentic coding models from Moonshot AI and Alibaba. Kimi K2.5 ships a 256K-token context window, while Qwen3.5-27B ships a 262K-token context window. On Google-Proof Q&A, Kimi K2.5 leads by 2.1 pts. On pricing, Qwen3.5-27B costs $0.2/1M input tokens versus $0.38/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-27B is ~96% cheaper at $0.2/1M; pay for Kimi K2.5 only for coding workflow support.
Specs
| Released | 2026-03-15 | 2026-02-24 |
| Context window | 256K | 262K |
| Parameters | 1T (MoE, 384 experts) | 27B |
| Architecture | mixture of experts | decoder only |
| License | MIT | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Kimi K2.5 | Qwen3.5-27B | |
|---|---|---|
| Input price | $0.38/1M tokens | $0.2/1M tokens |
| Output price | $1.72/1M tokens | $1.56/1M tokens |
| Providers |
Capabilities
| Kimi K2.5 | Qwen3.5-27B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Kimi K2.5 | Qwen3.5-27B |
|---|---|---|
| Google-Proof Q&A | 87.9 | 85.8 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Kimi K2.5 at 87.9 and Qwen3.5-27B at 85.8, with Kimi K2.5 ahead by 2.1 points. The largest visible gap is 2.1 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 reasoning mode: Qwen3.5-27B and tool use: Qwen3.5-27B. 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 Qwen3.5-27B lists $0.2/1M input and $1.56/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-27B lower by about $0.18 per million blended tokens. Availability is 7 providers versus 1, so concentration risk also matters.
Choose Kimi K2.5 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.5-27B when reasoning depth, larger context windows, and lower input-token cost 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 Qwen3.5-27B?
Qwen3.5-27B 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.
Which is cheaper, Kimi K2.5 or Qwen3.5-27B?
Qwen3.5-27B is cheaper on tracked token pricing. Kimi K2.5 costs $0.38/1M input and $1.72/1M output tokens. Qwen3.5-27B costs $0.2/1M input and $1.56/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2.5 or Qwen3.5-27B open source?
Kimi K2.5 is listed under MIT. Qwen3.5-27B 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 reasoning mode, Kimi K2.5 or Qwen3.5-27B?
Qwen3.5-27B has the clearer documented reasoning mode signal in this comparison. If reasoning mode 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 Qwen3.5-27B?
Both Kimi K2.5 and Qwen3.5-27B 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.
Where can I run Kimi K2.5 and Qwen3.5-27B?
Kimi K2.5 is available on Fireworks AI, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Qwen3.5-27B is available on OpenRouter. 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.