Kimi K2 Thinking Turbo vs Qwen3.7-Plus
Kimi K2 Thinking Turbo (2025) and Qwen3.7-Plus (2026) are frontier reasoning models from Moonshot AI and Alibaba. Kimi K2 Thinking Turbo ships a 262k-token context window, while Qwen3.7-Plus ships a 1m-token context window. On pricing, Qwen3.7-Plus costs $0.40/1M input tokens versus $1.15/1M 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.
Qwen3.7-Plus is ~187% cheaper at $0.40/1M; pay for Kimi K2 Thinking Turbo only for provider fit.
Decision scorecard
Local evidence first| Signal | Kimi K2 Thinking Turbo | Qwen3.7-Plus |
|---|---|---|
| Best for | general production evaluation | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Long context | Coding, RAG, and Agents |
| Context window | 262k | 1m |
| Cheapest output | $8/1M tokens | $1.60/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Local decision data tags Kimi K2 Thinking Turbo for Long context.
- Qwen3.7-Plus has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.7-Plus has the lower cheapest tracked output price at $1.60/1M tokens.
- Qwen3.7-Plus uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.7-Plus 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 Thinking Turbo
$2,920
Cheapest tracked route/tier: Vercel AI Gateway
Qwen3.7-Plus
$720
Cheapest tracked route/tier: Alibaba Cloud PAI-EAS
Estimated monthly gap: $2,200. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Kimi K2 Thinking Turbo and Qwen3.7-Plus; plan for SDK, billing, or endpoint changes.
- Qwen3.7-Plus is $6.40/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.7-Plus adds Vision, Multimodal, and Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.7-Plus and Kimi K2 Thinking Turbo; plan for SDK, billing, or endpoint changes.
- Kimi K2 Thinking Turbo is $6.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-11-06 | 2026-06-03 |
| Context window | 262k | 1m |
| Parameters | 1T (32B active) | — |
| 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 Thinking Turbo | Qwen3.7-Plus |
|---|---|---|
| Input price | $1.15/1M tokens | $0.40/1M tokens |
| Output price | $8/1M tokens | $1.60/1M tokens |
| Providers |
Capabilities
| Capability | Kimi K2 Thinking Turbo | Qwen3.7-Plus |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | 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 vision: Qwen3.7-Plus, multimodal input: Qwen3.7-Plus, reasoning mode: Qwen3.7-Plus, function calling: Qwen3.7-Plus, tool use: Qwen3.7-Plus, structured outputs: Qwen3.7-Plus, and code execution: Qwen3.7-Plus. Both models share the core language-model surface, 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 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider, while Qwen3.7-Plus lists $0.40/1M input and $1.60/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.7-Plus lower by about $2.45 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Kimi K2 Thinking Turbo when provider fit are central to the workload. Choose Qwen3.7-Plus when coding workflow support, larger context windows, 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Kimi K2 Thinking Turbo or Qwen3.7-Plus?
Qwen3.7-Plus supports 1m tokens, while Kimi K2 Thinking Turbo supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Kimi K2 Thinking Turbo or Qwen3.7-Plus?
Qwen3.7-Plus is cheaper on tracked token pricing. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Qwen3.7-Plus costs $0.40/1M input and $1.60/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2 Thinking Turbo or Qwen3.7-Plus open source?
Kimi K2 Thinking Turbo is listed under MIT. Qwen3.7-Plus 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 vision, Kimi K2 Thinking Turbo or Qwen3.7-Plus?
Qwen3.7-Plus 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 Thinking Turbo or Qwen3.7-Plus?
Qwen3.7-Plus 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 Thinking Turbo and Qwen3.7-Plus?
Kimi K2 Thinking Turbo is available on Vercel AI Gateway. Qwen3.7-Plus is available on Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.