Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.6
85
Qwen3.7 Max
93
Verified leaderboard positions: Kimi K2.6 #8 · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if agentic is the priority.
Agentic
+3.4 difference
Coding
+1.6 difference
Knowledge
+17.4 difference
Kimi K2.6
Qwen3.7 Max
$0.95 / $4
$null / $null
N/A
N/A
N/A
N/A
256K
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if agentic is the priority.
Qwen3.7 Max is clearly ahead on the provisional aggregate, 93 to 85. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Max's sharpest advantage is in knowledge, where it averages 71.2 against 53.8. The single biggest benchmark swing on the page is HLE, 34.7% to 41.4%. Kimi K2.6 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Qwen3.7 Max gives you the larger context window at 1M, compared with 256K for Kimi K2.6.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 93 to 85. The biggest single separator in this matchup is HLE, where the scores are 34.7% and 41.4%.
Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 71.2 versus 53.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.7 Max has the edge for coding in this comparison, averaging 73.6 versus 72. 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 69.7. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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