Kimi K2.5 vs Qwen3-235B-A22B
Kimi K2.5 (2026) and Qwen3-235B-A22B (2025) compare a coding-specialized model against a standalone API model. Kimi K2.5 ships a 256k-token context window, while Qwen3-235B-A22B ships a 128k-token context window. On MMLU PRO, Kimi K2.5 leads by 4.3 pts. On pricing, Qwen3-235B-A22B costs $0.09/1M input tokens versus $0.44/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Kimi K2.5 is coding-specialized model, while Qwen3-235B-A22B is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Kimi K2.5 | Qwen3-235B-A22B |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Long context |
| Context window | 256k | 128k |
| Cheapest output | $2/1M tokens | $0.58/1M tokens |
| Provider routes | 10 tracked | 5 tracked |
| Shared benchmarks | MMLU PRO leader | 3 shared |
Decision tradeoffs
- Kimi K2.5 holds a shared-benchmark lead on MMLU PRO, ahead by 4.3 points.
- Kimi K2.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.5 has broader tracked provider coverage for fallback and route flexibility.
- Kimi K2.5 uniquely exposes Vision, Multimodal, and JSON / Tool use in local model data.
- Local decision data tags Kimi K2.5 for Coding, RAG, and Agents.
- Qwen3-235B-A22B has the lower cheapest tracked output price at $0.58/1M tokens.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
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
Qwen3-235B-A22B
$217
Cheapest tracked route/tier: Novita AI
Estimated monthly gap: $635. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, AWS Bedrock, and OpenRouter; start route-level A/B tests there.
- Qwen3-235B-A22B is $1.42/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and JSON / Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI, OpenRouter, and AWS Bedrock; start route-level A/B tests there.
- Kimi K2.5 is $1.42/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Kimi K2.5 adds Vision, Multimodal, and JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-04-29 |
| Context window | 256k | 128k |
| Parameters | 1T (MoE, 384 experts) | 235B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Proprietary | Apache 2.0OSI-approved |
| Openness | Proprietary | Open source |
| Weights | Not released | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Kimi K2.5 | Qwen3-235B-A22B |
|---|---|---|
| Input price | $0.44/1M tokens | $0.09/1M tokens |
| Output price | $2/1M tokens | $0.58/1M tokens |
| Providers |
Capabilities
| Capability | Kimi K2.5 | Qwen3-235B-A22B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Kimi K2.5 | Qwen3-235B-A22B |
|---|---|---|
| MMLU PRO | 87.1 | 82.8 |
| Google-Proof Q&A | 87.9 | 86.1 |
| LiveCodeBench | 85.0 | 80.4 |
Continue comparing
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.