LLM Reference

Kimi K2 Thinking Turbo vs Qwen3.7-Max

Kimi K2 Thinking Turbo (2025) and Qwen3.7-Max (2026) are frontier reasoning models from Moonshot AI and Alibaba. Kimi K2 Thinking Turbo ships a 262k-token context window, while Qwen3.7-Max ships a 1m-token context window. On pricing, Kimi K2 Thinking Turbo costs $1.15/1M 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.

Qwen3.7-Max is safer overall; choose Kimi K2 Thinking Turbo when provider fit matters.

Decision scorecard

Local evidence first
SignalKimi K2 Thinking TurboQwen3.7-Max
Best forgeneral production evaluationreasoning-heavy apps, tool-calling agents, and long-context analysis
Decision fitLong contextCoding, RAG, and Agents
Context window262k1m
Cheapest output$8/1M tokens$3.75/1M tokens
Provider routes1 tracked4 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Kimi K2 Thinking Turbo when...
  • Local decision data tags Kimi K2 Thinking Turbo for Long context.
Choose Qwen3.7-Max when...
  • Qwen3.7-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.7-Max has the lower cheapest tracked output price at $3.75/1M tokens.
  • Qwen3.7-Max has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.7-Max uniquely exposes Reasoning, Function calling, and Tool use 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.

Lower estimate Qwen3.7-Max

Kimi K2 Thinking Turbo

$2,920

Cheapest tracked route/tier: Vercel AI Gateway

Qwen3.7-Max

$1,938

Cheapest tracked route/tier: Novita AI

Estimated monthly gap: $983. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Kimi K2 Thinking Turbo -> Qwen3.7-Max
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • Qwen3.7-Max is $4.25/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Qwen3.7-Max adds Reasoning, Function calling, and Tool use in local capability data.
Qwen3.7-Max -> Kimi K2 Thinking Turbo
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • Kimi K2 Thinking Turbo is $4.25/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.

Specs

Specification
Released2025-11-062026-05-19
Context window262k1m
Parameters1T (32B active)
Architecture-Decoder Only
LicenseMITOSI-approvedProprietary
OpennessOpen sourceProprietary
Commercial useCommercial use: permittedCommercial use: conditional
Knowledge cutoff--

Pricing and availability

Pricing attributeKimi K2 Thinking TurboQwen3.7-Max
Input price$1.15/1M tokens$1.25/1M tokens
Output price$8/1M tokens$3.75/1M tokens
Providers

Capabilities

CapabilityKimi K2 Thinking TurboQwen3.7-Max
VisionNoNo
MultimodalNoNo
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Qwen3.7-Max, function calling: Qwen3.7-Max, tool use: Qwen3.7-Max, structured outputs: Qwen3.7-Max, and code execution: Qwen3.7-Max. 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-Max lists $1.25/1M input and $3.75/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.7-Max lower by about $1.21 per million blended tokens. Availability is 1 providers versus 4, so concentration risk also matters.

Choose Kimi K2 Thinking Turbo 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.

FAQ

Which has a larger context window, Kimi K2 Thinking Turbo or Qwen3.7-Max?

Qwen3.7-Max 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-Max?

Qwen3.7-Max is cheaper on tracked token pricing. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M 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 Thinking Turbo or Qwen3.7-Max open source?

Kimi K2 Thinking Turbo 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 Thinking Turbo 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 Thinking Turbo or Qwen3.7-Max?

Qwen3.7-Max has the clearer documented function calling signal in this comparison. If function calling 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-Max?

Kimi K2 Thinking Turbo is available on Vercel AI Gateway. 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.