Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.6
84
Qwen3.6-35B-A3B
67
Verified leaderboard positions: Kimi K2.6 #6 · Qwen3.6-35B-A3B #20
Pick Kimi K2.6 if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Agentic
+21.6 difference
Coding
+5.1 difference
Knowledge
+6.7 difference
Multimodal
+3.6 difference
Kimi K2.6
Qwen3.6-35B-A3B
$0.95 / $4
N/A
N/A
N/A
N/A
N/A
256K
262K
Pick Kimi K2.6 if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Kimi K2.6 is clearly ahead on the provisional aggregate, 84 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.6's sharpest advantage is in agentic, where it averages 73.1 against 51.5. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 66.7% to 51.5%. Qwen3.6-35B-A3B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 256K for Kimi K2.6.
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 84 to 67. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 66.7% and 51.5%.
Qwen3.6-35B-A3B has the edge for knowledge tasks in this comparison, averaging 60.5 versus 53.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for coding in this comparison, averaging 72 versus 66.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.1 versus 51.5. Inside this category, Toolathlon is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for multimodal and grounded tasks in this comparison, averaging 79.7 versus 76.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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