Kimi K2 vs Qwen3.7-Max
Kimi K2 (2025) and Qwen3.7-Max (2026) are frontier reasoning models from Moonshot AI and Alibaba. Kimi K2 ships a 262k-token context window, while Qwen3.7-Max ships a 1m-token context window. On pricing, Kimi K2 costs $0.50/1M input tokens versus $1.25/1M 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.
Kimi K2 is ~150% cheaper at $0.50/1M; pay for Qwen3.7-Max only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Kimi K2 | Qwen3.7-Max |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | reasoning-heavy apps, tool-calling agents, and long-context analysis |
| Decision fit | RAG, Agents, and Long context | Coding, RAG, and Agents |
| Context window | 262k | 1m |
| Cheapest output | $2/1M tokens | $3.75/1M tokens |
| Provider routes | 3 tracked | 4 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Kimi K2 has the lower cheapest tracked output price at $2/1M tokens.
- Local decision data tags Kimi K2 for RAG, Agents, and Long context.
- Qwen3.7-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.7-Max has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.7-Max uniquely exposes Reasoning, Tool use, and Code execution in local model data.
- Local decision data tags Qwen3.7-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
$900
Cheapest tracked route/tier: AWS Bedrock
Qwen3.7-Max
$1,938
Cheapest tracked route/tier: Novita AI
Estimated monthly gap: $1,038. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3.7-Max is $1.75/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.7-Max adds Reasoning, Tool use, and Code execution in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Kimi K2 is $1.75/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Tool use, and Code execution before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-07-11 | 2026-05-19 |
| Context window | 262k | 1m |
| Parameters | 1K | — |
| Architecture | - | Decoder Only |
| License | MITOSI-approved | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Kimi K2 | Qwen3.7-Max |
|---|---|---|
| Input price | $0.50/1M tokens | $1.25/1M tokens |
| Output price | $2/1M tokens | $3.75/1M tokens |
| Providers |
Capabilities
| Capability | Kimi K2 | Qwen3.7-Max |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Qwen3.7-Max, tool use: Qwen3.7-Max, and code execution: Qwen3.7-Max. 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 lists $0.50/1M input and $2/1M output tokens on the cheapest tracked provider, while Qwen3.7-Max lists $1.25/1M input and $3.75/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2 lower by about $1.05 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.
Choose Kimi K2 when provider fit and lower input-token cost are central to the workload. Choose Qwen3.7-Max when coding workflow support, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Kimi K2 or Qwen3.7-Max?
Qwen3.7-Max supports 1m tokens, while Kimi K2 supports 262k 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 or Qwen3.7-Max?
Kimi K2 is cheaper on tracked token pricing. Kimi K2 costs $0.50/1M input and $2/1M output tokens. Qwen3.7-Max costs $1.25/1M input and $3.75/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2 or Qwen3.7-Max open source?
Kimi K2 is listed under MIT. Qwen3.7-Max is listed under Proprietary. 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 or Qwen3.7-Max?
Qwen3.7-Max 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 or Qwen3.7-Max?
Both Kimi K2 and Qwen3.7-Max 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 and Qwen3.7-Max?
Kimi K2 is available on OpenRouter, AWS Bedrock, and GCP Vertex AI. Qwen3.7-Max is available on Alibaba Cloud PAI-EAS, Vercel AI Gateway, Novita AI, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.