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Model comparison

Kimi K2.7 Code vs Qwen3.6-35B-A3B

Data verified

Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

Moonshot AI
54.03/100
Margin
3.6pts
← winning
50.46/100
0 category wins0 category wins

Public leaderboard positions: Kimi K2.7 Code #92 (Estimated); Qwen3.6-35B-A3B #109 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Kimi K2.7 Code and Qwen3.6-35B-A3B share 16 comparable benchmark results. 0 of 8 categories are comparable. 7 results are unique to Kimi K2.7 Code; 41 to Qwen3.6-35B-A3B.

Updated July 27, 2026
Shared results
16
Kimi K2.7 Code only
7
Qwen3.6-35B-A3B only
41
Comparable categories
0 / 8

Benchmark data for Kimi K2.7 Code and Qwen3.6-35B-A3B is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 16 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.

Qwen3.6-35B-A3B has the larger context window at 262K, compared with 256K for Kimi K2.7 Code.

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 Qwen3.6-35B-A3B
CategoryKimi K2.7 CodeΔQwen3.6-35B-A3B
AgenticKimi K2.7 CodeNot measuredMarginNo overlapQwen3.6-35B-A3B51.5
CodingKimi K2.7 CodeNot measuredMarginNo overlapQwen3.6-35B-A3B73.8
KnowledgeKimi K2.7 CodeNot measuredMarginNo overlapQwen3.6-35B-A3B51.4
MathKimi K2.7 CodeNot measuredMarginNo overlapQwen3.6-35B-A3B88.2
MultimodalKimi K2.7 CodeNot measuredMarginNo overlapQwen3.6-35B-A3B76.3

Operational comparison

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

MetricKimi K2.7 CodeQwen3.6-35B-A3BComparison
Input / output priceUSD per 1M tokensKimi K2.7 Code$0.95 input / $4 outputQwen3.6-35B-A3BNot availableA complete price comparison is not available.
Generation speedtokens per secondKimi K2.7 CodeNot availableQwen3.6-35B-A3BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenKimi K2.7 CodeNot availableQwen3.6-35B-A3BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensKimi K2.7 Code256KQwen3.6-35B-A3B262KQwen3.6-35B-A3B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
Kimi Claw 24/7Source 46.9%Not comparable
MCP AtlasSource 76%62.8%Kimi K2.7 Code leads
MCP Mark VerifiedSource 81.1%Not comparable
AA Agentic IndexSource 29.6%21.4%Kimi K2.7 Code leads
τ²-bench resultsSource 90.1%95.3%Qwen3.6-35B-A3B leads
GDPval-AASource 34.3%27.6%Kimi K2.7 Code leads
GDPval-AASource 11861052Kimi K2.7 Code leads
Terminal-Bench 2.0Source 51.5%Not comparable
Claw-EvalSource 68.7%Not comparable
QwenClawBenchSource 52.6%Not comparable
QwenWebBenchSource 1397Not comparable
τ³-bench resultsSource 67.2%Not comparable
VITA-BenchSource 35.6%Not comparable
DeepPlanningSource 25.9%Not comparable
ToolathlonSource 26.9%Not comparable
WideResearchSource 60.1%Not comparable
Gert LabsSource 42.65%Not comparable
Coding
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
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%41.9%Kimi K2.7 Code leads
AA-SciCodeSource 47.5%35.8%Kimi K2.7 Code leads
SWE-bench VerifiedSource 73.4%Not comparable
SWE MultilingualSource 67.2%Not comparable
SWE-bench ProSource 49.5%Not comparable
Terminal-Bench 2.0Source 51.5%Not comparable
LiveCodeBenchSource 80.4%Not comparable
NL2RepoSource 29.4%Not comparable
Reasoning
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
AA-LCRSource 66.3%63.7%Kimi K2.7 Code leads
CritPtSource 10.0%0.3%Kimi K2.7 Code leads
Knowledge
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
Artificial Analysis Intelligence IndexSource 42.0%31.6%Kimi K2.7 Code leads
AA-GPQA DiamondSource 89.6%84.1%Kimi K2.7 Code leads
AA-HLESource 32.8%20.2%Kimi K2.7 Code leads
AA-Omniscience IndexSource -10.7%-21.4%Kimi K2.7 Code leads
AA-Omniscience AccuracySource 38.6%18.9%Kimi K2.7 Code leads
AA-Omniscience Hallucination RateSource 80.3%49.7%Qwen3.6-35B-A3B leads
MMLU-ProSource 85.2%Not comparable
SuperGPQASource 64.7%Not comparable
C-EvalSource 90%Not comparable
GPQASource 86%Not comparable
HLESource 21.4%Not comparable
Math
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
HMMT Feb 2025Source 90.7%Not comparable
HMMT Nov 2025Source 89.1%Not comparable
HMMT Feb 2026Source 83.6%Not comparable
MMAnswerBenchSource 78.9%Not comparable
AIME26Source 92.7%Not comparable
Multimodal
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
Design Arena WebsiteSource 1300Not comparable
MMMUSource 81.7%Not comparable
MMMU-ProSource 75.3%Not comparable
RealWorldQASource 85.3%Not comparable
OmniDocBench 1.5Source 89.9%Not comparable
CharXivSource 78%Not comparable
SimpleVQASource 58.9%Not comparable
CC-OCRSource 81.9%Not comparable
AI2D_TESTSource 92.7%Not comparable
RefCOCO (avg)Source 92.0%Not comparable
ODINW13Source 50.8%Not comparable
Video-MME (with subtitle)Source 86.6%Not comparable
Video-MME (w/o subtitle)Source 82.5%Not comparable
VideoMMMUSource 83.7%Not comparable
MLVU (M-Avg)Source 86.2%Not comparable
AA-MMMU-ProSource 75.0%Not comparable
Inst. Following
BenchmarkKimi K2.7 CodeQwen3.6-35B-A3BResult
AA-IFBenchSource 63.1%64.4%Qwen3.6-35B-A3B leads
Frequently Asked Questions (3)

Can I compare Kimi K2.7 Code and Qwen3.6-35B-A3B 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 Qwen3.6-35B-A3B 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
Qwen3.6-35B-A3B
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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