Kimi K2.5 vs Qwen3.7 Max

At a Glance

Compare
Kimi K2.5Moonshot AI
Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#13 of 44$0.057 per LiveBench case
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.45Deepinfra · Aug 29, 2026$1.475Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokens$2.25Deepinfra · Aug 29, 2026$4.425Openrouter · Sep 22, 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-K2.5Qwen3.7 Max
DeveloperMoonshot AIQwen
FamilyKimi K2 5Qwen3 7
ModelKimi-K2.5Qwen3.7 Max
VersionKimi-K2.5Qwen3.7 Max
Lifecycleactiveactive
Released2026-01-272026-05-20
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Video
Output modalitiesTextText
Context window262K1,000K
Total parameters1TUnknown
Active parameters32BUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generation, reasoning, toolsagents, chat, generation, reasoning, structured_outputs, tools, vision

Kimi K2.5 Capabilities

chatgenerationreasoningtools
Serving providers3
Canonical IDmoonshotai/Kimi-K2.5

Qwen3.7 Max Capabilities

agentschatgenerationreasoningstructured outputstoolsvision
Serving providers4
Canonical IDqwen/qwen3.7-max

Primary Evidence

Sources and Freshness

Questions

Kimi K2.5 vs Qwen3.7 Max FAQs

Is Kimi K2.5 or Qwen3.7 Max better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2.5 and Qwen3.7 Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Kimi K2.5 or Qwen3.7 Max?+

Kimi K2.5 is $0.45 and Qwen3.7 Max is $1.475 per million tokens, so Kimi K2.5 is cheaper on this metric. Kimi K2.5 is $2.25 and Qwen3.7 Max is $4.425 per million tokens, so Kimi K2.5 is cheaper on this metric.

Which has a larger context window, Kimi K2.5 or Qwen3.7 Max?+

Qwen3.7 Max has the larger sourced context window. Kimi K2.5 supports 262K and Qwen3.7 Max supports 1,000K.

Which performs better in benchmarks, Kimi K2.5 or Qwen3.7 Max?+

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

Can Kimi K2.5 or Qwen3.7 Max be self-hosted?+

Kimi K2.5 is the only model in this pair currently marked as self-hostable. Kimi K2.5 is open weight; Qwen3.7 Max is not marked open weight.

Can Kimi K2.5 and Qwen3.7 Max understand images?+

Kimi K2.5 is documented with image input; Qwen3.7 Max is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Kimi K2.5 or Qwen3.7 Max?+

Neither has a larger sourced maximum output. Kimi K2.5 is — and Qwen3.7 Max is 66K.

Do Kimi K2.5 and Qwen3.7 Max support reasoning and tool use?+

Kimi K2.5: reasoning, tool calling, and image input. Qwen3.7 Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Kimi K2.5 or Qwen3.7 Max?+

Kimi K2.5 has 3 sourced provider routes; Qwen3.7 Max has 4, so Qwen3.7 Max has broader tracked availability.

Which offers better value, Kimi K2.5 or Qwen3.7 Max?+

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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