Kimi K2 Thinking vs Qwen3.7 Flash

At a Glance

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Kimi K2 ThinkingMoonshot AI
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.60Openrouter · Sep 23, 2026$0.030Openrouter · Sep 23, 2026
Output priceFrom · USD / 1M tokens$2.50Openrouter · Sep 23, 2026$0.13Openrouter · Sep 23, 2026
Context windowMaximum documented tokens262K1,000K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldKimi-K2-ThinkingQwen3.7 Flash
DeveloperMoonshot AIQwen
FamilyKimi K2 ThinkingQwen3 7
ModelKimi-K2-ThinkingQwen3.7 Flash
VersionKimi-K2-ThinkingQwen3.7 Flash
Lifecycleactiveactive
Released2025-11-062026-07-15
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video
Output modalitiesTextText
Context window262K1,000K
Total parameters1TUnknown
Active parameters32BUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessHugging Face (Standard), Openrouter (Standard)Alibaba Cloud Model Studio (Standard), Openrouter (Standard)
Capabilitieschat, generation, reasoning, toolsagents, chat, generation, reasoning, structured_outputs, tools, vision

Kimi K2 Thinking Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDmoonshotai/Kimi-K2-Thinking

Qwen3.7 Flash Capabilities

agentschatgenerationreasoningstructured outputstoolsvision
Serving providers2
Canonical IDqwen/qwen3.7-flash

Primary Evidence

Sources and Freshness

Questions

Kimi K2 Thinking vs Qwen3.7 Flash FAQs

Is Kimi K2 Thinking or Qwen3.7 Flash better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2 Thinking and Qwen3.7 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Kimi K2 Thinking or Qwen3.7 Flash?+

Kimi K2 Thinking is $0.60 and Qwen3.7 Flash is $0.030 per million tokens, so Qwen3.7 Flash is cheaper on this metric. Kimi K2 Thinking is $2.50 and Qwen3.7 Flash is $0.13 per million tokens, so Qwen3.7 Flash is cheaper on this metric.

Which has a larger context window, Kimi K2 Thinking or Qwen3.7 Flash?+

Qwen3.7 Flash has the larger sourced context window. Kimi K2 Thinking supports 262K and Qwen3.7 Flash supports 1,000K.

Which performs better in benchmarks, Kimi K2 Thinking or Qwen3.7 Flash?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Kimi K2 Thinking or Qwen3.7 Flash be self-hosted?+

Kimi K2 Thinking is the only model in this pair currently marked as self-hostable. Kimi K2 Thinking is open weight; Qwen3.7 Flash is not marked open weight.

Can Kimi K2 Thinking and Qwen3.7 Flash understand images?+

Kimi K2 Thinking is not documented with image input; Qwen3.7 Flash is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Kimi K2 Thinking or Qwen3.7 Flash?+

Kimi K2 Thinking has the larger sourced maximum output: Kimi K2 Thinking supports 131K and Qwen3.7 Flash supports 66K output tokens.

Do Kimi K2 Thinking and Qwen3.7 Flash support reasoning and tool use?+

Kimi K2 Thinking: reasoning and tool calling. Qwen3.7 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Kimi K2 Thinking or Qwen3.7 Flash?+

Kimi K2 Thinking has 2 sourced provider routes; Qwen3.7 Flash has 2, a tie.

Which offers better value, Kimi K2 Thinking or Qwen3.7 Flash?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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