Kimi K2.5 vs Qwen3-Max
Kimi K2.5 (2026) and Qwen3-Max (2025) compare a coding-specialized model against a standalone API model. Kimi K2.5 ships a 256k-token context window, while Qwen3-Max ships a 262k-token context window. On SWE-bench Verified, Qwen3-Max leads by 2 pts. On pricing, Kimi K2.5 costs $0.44/1M input tokens; Qwen3-Max ranges from $1.20 to $3/1M input tokens by tier. 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-Max 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-Max |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 256k | 262k |
| Cheapest output | $2/1M tokens | $3.90/1M tokens |
| Provider routes | 10 tracked | 3 tracked |
| Shared benchmarks | 4 rows | SWE-bench Verified leader |
Decision tradeoffs
- Kimi K2.5 holds a shared-benchmark lead on MultiChallenge, ahead by 20.2 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 procurement flexibility.
- Local decision data tags Kimi K2.5 for Coding, RAG, and Agents.
- Qwen3-Max holds a shared-benchmark lead on SWE-bench Verified, ahead by 2 points.
- Qwen3-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3-Max uniquely exposes Tool use in local model data.
- Local decision data tags Qwen3-Max 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-Max
$1,599
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $747. 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-Max is $1.90/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3-Max adds Tool use 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 $1.90/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-04-28 |
| Context window | 256k | 262k |
| Parameters | 1T (MoE, 384 experts) | — |
| 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 | - | 2025-12 |
Pricing and availability
| Pricing attribute | Kimi K2.5 | Qwen3-Max |
|---|---|---|
| Input price | $0.44/1M tokens |
|
| Output price | $2/1M tokens |
|
| Providers |
Capabilities
| Capability | Kimi K2.5 | Qwen3-Max |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | No | Yes |
| 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-Max |
|---|---|---|
| SWE-bench Verified | 76.8 | 78.8 |
| MultiChallenge | 61.4 | 41.2 |
| Berkeley Function Calling Leaderboard v3 | 64.5 | 71.9 |
| τ-bench | 74.2 | 76.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has Kimi K2.5 at 76.8 and Qwen3-Max at 78.8, with Qwen3-Max ahead by 2 points; MultiChallenge has Kimi K2.5 at 61.4 and Qwen3-Max at 41.2, with Kimi K2.5 ahead by 20.2 points; Berkeley Function Calling Leaderboard v3 has Kimi K2.5 at 64.5 and Qwen3-Max at 71.9, with Qwen3-Max ahead by 7.4 points. The largest visible gap is 20.2 points on MultiChallenge, 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 tool use: Qwen3-Max. Both models share vision, multimodal input, 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 $0.44/1M input and $2/1M output tokens on the cheapest tracked provider, while Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. A 70/30 input-output blend puts Kimi K2.5 lower by about $0.81 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 10 providers versus 3, so concentration risk also matters.
Choose Kimi K2.5 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3-Max when long-context analysis 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-Max?
Qwen3-Max 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-Max?
Kimi K2.5 lists $0.44/1M input and $2/1M output tokens on the cheapest tracked provider. Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2.5 or Qwen3-Max open source?
Kimi K2.5 is listed under Proprietary. Qwen3-Max 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-Max?
Both Kimi K2.5 and Qwen3-Max expose vision. 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 multimodal input, Kimi K2.5 or Qwen3-Max?
Both Kimi K2.5 and Qwen3-Max expose multimodal input. 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-Max?
Kimi K2.5 is available on Cloudflare Workers AI, Fireworks AI, OpenRouter, Together AI, and NVIDIA NIM. Qwen3-Max is available on OpenRouter, Vercel AI Gateway, 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.