Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1
58
Kimi K2.5
64
Verified leaderboard positions: GPT-4.1 unranked · Kimi K2.5 #11
Pick Kimi K2.5 if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Coding
+9.6 difference
Knowledge
+1.2 difference
Inst. Following
+6.5 difference
GPT-4.1
Kimi K2.5
$2 / $8
$0.6 / $3
108 t/s
45 t/s
1.02s
2.38s
1M
256K
Pick Kimi K2.5 if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Kimi K2.5 is clearly ahead on the provisional aggregate, 64 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in coding, where it averages 64.2 against 54.6. The single biggest benchmark swing on the page is SWE-bench Verified, 54.6% to 76.8%. GPT-4.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 2.7x on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 64 to 58. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 54.6% and 76.8%.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 65.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for coding in this comparison, averaging 64.2 versus 54.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for instruction following in this comparison, averaging 93.9 versus 87.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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