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Model comparison

Kimi K2.7 Code vs Qwen 3.6 Max (preview)

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

Moonshot AI
54.03/100
Margin
5.3pts
winning →
59.29/100
0 category wins0 category wins

Public leaderboard positions: Kimi K2.7 Code #92 (Estimated); Qwen 3.6 Max (preview) #56 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Kimi K2.7 Code and Qwen 3.6 Max (preview) share 11 comparable benchmark results. 0 of 8 categories are comparable. 12 results are unique to Kimi K2.7 Code; 10 to Qwen 3.6 Max (preview).

Updated July 27, 2026
Shared results
11
Kimi K2.7 Code only
12
Qwen 3.6 Max (preview) only
10
Comparable categories
0 / 8

Benchmark data for Kimi K2.7 Code and Qwen 3.6 Max (preview) is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Kimi K2.7 Code and Qwen 3.6 Max (preview)
CategoryKimi K2.7 CodeΔQwen 3.6 Max (preview)
AgenticKimi K2.7 CodeNot measuredMarginNo overlapQwen 3.6 Max (preview)65.4
CodingKimi K2.7 CodeNot measuredMarginNo overlapQwen 3.6 Max (preview)51.0
KnowledgeKimi K2.7 CodeNot measuredMarginNo overlapQwen 3.6 Max (preview)73.9
MathKimi K2.7 CodeNot measuredMarginNo overlapQwen 3.6 Max (preview)18.4

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricKimi K2.7 CodeQwen 3.6 Max (preview)Comparison
Input / output priceUSD per 1M tokensKimi K2.7 Code$0.95 input / $4 outputQwen 3.6 Max (preview)Not availableA complete price comparison is not available.
Generation speedtokens per secondKimi K2.7 CodeNot availableQwen 3.6 Max (preview)Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenKimi K2.7 CodeNot availableQwen 3.6 Max (preview)Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensKimi K2.7 Code256KQwen 3.6 Max (preview)256KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
Kimi Claw 24/7Source 46.9%Not comparable
MCP AtlasSource 76%Not comparable
MCP Mark VerifiedSource 81.1%Not comparable
AA Agentic IndexSource 29.6%Not comparable
τ²-bench resultsSource 90.1%95.9%Qwen 3.6 Max (preview) leads
GDPval-AASource 34.3%Not comparable
GDPval-AASource 1186Not comparable
Terminal-Bench 2.0Source 65.4%Not comparable
QwenClawBenchSource 59.0%Not comparable
QwenWebBenchSource 1532Not comparable
Coding
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
Kimi Code Bench v2Source 62.0%Not comparable
ProgramBenchSource 53.6%Not comparable
MLS-Bench LiteSource 35.1%Not comparable
cursorBench32Source 49.7%Not comparable
AA Coding IndexSource 60.8%Not comparable
AA-SciCodeSource 47.5%46.9%Kimi K2.7 Code leads
SWE-bench ProSource 57.3%Not comparable
SciCodeSource 47%Not comparable
NL2RepoSource 42.9%Not comparable
Terminal-Bench 2.0Source 65.4%Not comparable
Reasoning
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
AA-LCRSource 66.3%69.7%Qwen 3.6 Max (preview) leads
CritPtSource 10.0%3.7%Kimi K2.7 Code leads
Knowledge
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
Artificial Analysis Intelligence IndexSource 42.0%40.0%Kimi K2.7 Code leads
AA-GPQA DiamondSource 89.6%88.8%Kimi K2.7 Code leads
AA-HLESource 32.8%28.9%Kimi K2.7 Code leads
AA-Omniscience IndexSource -10.7%10.2%Qwen 3.6 Max (preview) leads
AA-Omniscience AccuracySource 38.6%37.7%Kimi K2.7 Code leads
AA-Omniscience Hallucination RateSource 80.3%44.2%Qwen 3.6 Max (preview) leads
SuperGPQASource 73.9%Not comparable
Math
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
FrontierMath v2 (Tiers 1-3)Source 23.103%Not comparable
FrontierMath v2 (Tier 4)Source 4.167%Not comparable
Multimodal
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
Design Arena WebsiteSource 1300Not comparable
Inst. Following
BenchmarkKimi K2.7 CodeQwen 3.6 Max (preview)Result
AA-IFBenchSource 63.1%76.6%Qwen 3.6 Max (preview) leads
Frequently Asked Questions (3)

Can I compare Kimi K2.7 Code and Qwen 3.6 Max (preview) on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Kimi K2.7 Code and Qwen 3.6 Max (preview) today?

Kimi K2.7 Code: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Kimi K2.7 Code
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Qwen 3.6 Max (preview)
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 27, 2026

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