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 rows |
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 procurement flexibility.
- Kimi K2.5 uniquely exposes Vision, Multimodal, and Function calling 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 Function calling 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 Function calling 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 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| 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 |
| Function calling | Yes | No |
| Tool use | No | 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 |
Deep dive
On shared benchmark coverage, MMLU PRO has Kimi K2.5 at 87.1 and Qwen3-235B-A22B at 82.8, with Kimi K2.5 ahead by 4.3 points; Google-Proof Q&A has Kimi K2.5 at 87.9 and Qwen3-235B-A22B at 86.1, with Kimi K2.5 ahead by 1.8 points; LiveCodeBench has Kimi K2.5 at 85 and Qwen3-235B-A22B at 80.4, with Kimi K2.5 ahead by 4.6 points. The largest visible gap is 4.6 points on LiveCodeBench, 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: Kimi K2.5, multimodal input: Kimi K2.5, and function calling: Kimi K2.5. Both models share 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 $0.44/1M input and $2/1M output tokens on the cheapest tracked provider, while Qwen3-235B-A22B lists $0.09/1M input and $0.58/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-235B-A22B lower by about $0.67 per million blended tokens. Availability is 10 providers versus 5, so concentration risk also matters.
Choose Kimi K2.5 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Qwen3-235B-A22B when provider fit 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 Qwen3-235B-A22B?
Kimi K2.5 supports 256k tokens, while Qwen3-235B-A22B supports 128k 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 Qwen3-235B-A22B?
Qwen3-235B-A22B is cheaper on tracked token pricing. Kimi K2.5 costs $0.44/1M input and $2/1M output tokens. Qwen3-235B-A22B costs $0.09/1M input and $0.58/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2.5 or Qwen3-235B-A22B open source?
Kimi K2.5 is listed under Proprietary. Qwen3-235B-A22B 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 vision, Kimi K2.5 or Qwen3-235B-A22B?
Kimi K2.5 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Kimi K2.5 or Qwen3-235B-A22B?
Kimi K2.5 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 Qwen3-235B-A22B?
Kimi K2.5 is available on Cloudflare Workers AI, Fireworks AI, OpenRouter, Together AI, and NVIDIA NIM. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, Venice AI, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.