Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude 3.5 Sonnet
41
Kimi K2.6
84
Verified leaderboard positions: Claude 3.5 Sonnet unranked · Kimi K2.6 #6
Pick Kimi K2.6 if you want the stronger benchmark profile. Claude 3.5 Sonnet only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+23.0 difference
Knowledge
+5.6 difference
Claude 3.5 Sonnet
Kimi K2.6
$3 / $15
$0.95 / $4
N/A
N/A
N/A
N/A
200K
256K
Pick Kimi K2.6 if you want the stronger benchmark profile. Claude 3.5 Sonnet only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Kimi K2.6 is clearly ahead on the provisional aggregate, 84 to 41. 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 coding, where it averages 72 against 49. The single biggest benchmark swing on the page is SWE-bench Verified, 49% to 80.2%. Claude 3.5 Sonnet does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude 3.5 Sonnet is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 3.8x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while Claude 3.5 Sonnet 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. Kimi K2.6 gives you the larger context window at 256K, compared with 200K for Claude 3.5 Sonnet.
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 84 to 41. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49% and 80.2%.
Claude 3.5 Sonnet has the edge for knowledge tasks in this comparison, averaging 59.4 versus 53.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.6 has the edge for coding in this comparison, averaging 72 versus 49. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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