Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 4.6
85
Kimi K2.5 (Reasoning)
79
Pick Claude Sonnet 4.6 if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Agentic
+10.7 difference
Coding
+10.4 difference
Knowledge
+13.6 difference
Claude Sonnet 4.6
Kimi K2.5 (Reasoning)
$3 / $15
$null / $null
44 t/s
N/A
1.48s
N/A
200K
128K
Pick Claude Sonnet 4.6 if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Claude Sonnet 4.6 is clearly ahead on the provisional aggregate, 85 to 79. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Sonnet 4.6's sharpest advantage is in agentic, where it averages 65.3 against 54.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 59.1% to 50.8%. Kimi K2.5 (Reasoning) does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 (Reasoning) is the reasoning model in the pair, while Claude Sonnet 4.6 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. Claude Sonnet 4.6 gives you the larger context window at 200K, compared with 128K for Kimi K2.5 (Reasoning).
Claude Sonnet 4.6 is ahead on BenchLM's provisional leaderboard, 85 to 79. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 59.1% and 50.8%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 73.7. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 66.4. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Claude Sonnet 4.6 has the edge for agentic tasks in this comparison, averaging 65.3 versus 54.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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