Kimi K2.5 vs Qwen3.6-27B
Kimi K2.5 (2026) and Qwen3.6-27B (2026) are agentic coding models from Moonshot AI and Alibaba. Kimi K2.5 ships a 256k-token context window, while Qwen3.6-27B ships a 262k-token context window. On MMLU PRO, Kimi K2.5 leads by 0.9 pts. On pricing, Qwen3.6-27B costs $0.32/1M input tokens versus $0.44/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen3.6-27B is safer overall; choose Kimi K2.5 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Kimi K2.5 | Qwen3.6-27B |
|---|---|---|
| Best for | custom coding agents, code generation, and tool loops | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 256k | 262k |
| Cheapest output | $2/1M tokens | $3.20/1M tokens |
| Provider routes | 10 tracked | 4 tracked |
| Shared benchmarks | MMLU PRO leader | 6 shared |
Decision tradeoffs
- Kimi K2.5 holds a shared-benchmark lead on MMLU PRO, ahead by 0.9 points.
- Kimi K2.5 has the lower cheapest tracked output price at $2/1M tokens.
- Kimi K2.5 has broader tracked provider coverage for fallback and route flexibility.
- Kimi K2.5 uniquely exposes Structured outputs in local model data.
- Local decision data tags Kimi K2.5 for Coding, RAG, and Agents.
- Qwen3.6-27B holds a shared-benchmark lead on SWE-bench Verified, ahead by 0.4 points.
- Qwen3.6-27B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.6-27B uniquely exposes Reasoning in local model data.
- Local decision data tags Qwen3.6-27B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Kimi K2.5
$852
Cheapest tracked route/tier: OpenRouter
Qwen3.6-27B
$1,056
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $204. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Vercel AI Gateway, and Novita AI; start route-level A/B tests there.
- Qwen3.6-27B is $1.20/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Qwen3.6-27B adds Reasoning in local capability data.
- Provider overlap exists on OpenRouter, Vercel AI Gateway, and Novita AI; start route-level A/B tests there.
- Kimi K2.5 is $1.20/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
- Kimi K2.5 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2026-04-27 |
| Context window | 256k | 262k |
| Parameters | 1T (MoE, 384 experts) | 27B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Proprietary | Apache 2.0OSI-approved |
| Openness | Proprietary | Open source |
| Weights | Not released | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Kimi K2.5 | Qwen3.6-27B |
|---|---|---|
| Input price | $0.44/1M tokens | $0.32/1M tokens |
| Output price | $2/1M tokens | $3.20/1M tokens |
| Providers |
Capabilities
| Capability | Kimi K2.5 | Qwen3.6-27B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| JSON / Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Kimi K2.5 | Qwen3.6-27B |
|---|---|---|
| MMLU PRO | 87.1 | 86.2 |
| SWE-bench Verified | 76.8 | 77.2 |
| Google-Proof Q&A | 87.9 | 87.8 |
| LiveCodeBench | 85.0 | 83.9 |
| Humanity's Last Exam | 50.2 | 24.0 |
| MMMU Pro | 78.5 | 75.8 |
Continue comparing
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.