Model comparison
Kimi K2 vs Qwen3.6-35B-A3B
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Kimi K2 unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: Kimi K2 supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2 and Qwen3.6-35B-A3B share 12 comparable benchmark results. 1 of 8 categories are comparable. 3 results are unique to Kimi K2; 46 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 12
- Kimi K2 only
- 3
- Qwen3.6-35B-A3B only
- 46
- Comparable categories
- 1 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. Kimi K2 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 59 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in mathematics, where it averages 88.2 against 16.1.
Qwen3.6-35B-A3B is the reasoning model in the pair, while Kimi K2 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 128K for Kimi K2.
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 | Kimi K2 | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | Kimi K216.1 | Margin→ 72.1 | Qwen3.6-35B-A3B88.2 |
| Agentic | Kimi K2Not measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Coding | Kimi K2Not measured | MarginNo overlap | Qwen3.6-35B-A3B73.8 |
| Knowledge | Kimi K2Not measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Multimodal | Kimi K2Not measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2 | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2$0.6 input / $2.5 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Kimi K243 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K21.51 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2128K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 61.1% | 95.3% | Qwen3.6-35B-A3B leads |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| Claw-EvalSource | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
Coding9 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Terminal-Bench HardSource | 15.9% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 34.5% | 35.8% | Qwen3.6-35B-A3B 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 |
| AA Coding IndexSource | — | 41.9% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 19.4% | 31.6% | Qwen3.6-35B-A3B leads |
| AA-GPQA DiamondSource | 76.6% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 7.0% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -27.5% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 26.8% | 18.9% | Kimi K2 leads |
| AA-Omniscience Hallucination RateSource | 74.2% | 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 |
MathQwen3.6-35B-A3B wins7 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 21.404% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 0.000% | — | Not comparable |
| 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 |
Multimodal16 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1085 | — | Not 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. Following1 benchmarks
| Benchmark | Kimi K2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 41.5% | 64.4% | Qwen3.6-35B-A3B leads |
Frequently Asked Questions (2)
Which is better, Kimi K2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 59 to 43.
Which is better for math, Kimi K2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 16.1. Kimi K2 stays close enough that the answer can still flip depending on your workload.
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