Head-to-head comparison across 5benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Sonnet 4.5
67
Kimi K2.5
68
Verified leaderboard positions: Claude Sonnet 4.5 unranked · Kimi K2.5 #9
Pick Kimi K2.5 if you want the stronger benchmark profile. Claude Sonnet 4.5 only becomes the better choice if knowledge is the priority.
Agentic
+0.7 difference
Coding
+13.0 difference
Reasoning
+47.4 difference
Knowledge
+18.3 difference
Math
+9.1 difference
Claude Sonnet 4.5
Kimi K2.5
$3 / $15
$0.5 / $2.8
N/A
45 t/s
N/A
2.38s
200K
256K
Pick Kimi K2.5 if you want the stronger benchmark profile. Claude Sonnet 4.5 only becomes the better choice if knowledge is the priority.
Kimi K2.5 finishes one point ahead on BenchLM's provisional leaderboard, 68 to 67. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Kimi K2.5's sharpest advantage is in reasoning, where it averages 61 against 13.6. The single biggest benchmark swing on the page is AIME 2025, 87% to 96.1%. Claude Sonnet 4.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 4.5 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.50 input / $2.80 output per 1M tokens for Kimi K2.5. That is roughly 5.4x on output cost alone. Kimi K2.5 gives you the larger context window at 256K, compared with 200K for Claude Sonnet 4.5.
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 68 to 67. The biggest single separator in this matchup is AIME 2025, where the scores are 87% and 96.1%.
Claude Sonnet 4.5 has the edge for knowledge tasks in this comparison, averaging 83.4 versus 65.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Sonnet 4.5 has the edge for coding in this comparison, averaging 77.2 versus 64.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for math in this comparison, averaging 96.1 versus 87. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for reasoning in this comparison, averaging 61 versus 13.6. Claude Sonnet 4.5 stays close enough that the answer can still flip depending on your workload.
Claude Sonnet 4.5 has the edge for agentic tasks in this comparison, averaging 55.3 versus 54.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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