Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Command A+
32
Kimi K2.5
64
Verified leaderboard positions: Command A+ unranked · Kimi K2.5 #13
Pick Kimi K2.5 if you want the stronger benchmark profile. Command A+ only becomes the better choice if you want the stronger reasoning-first profile.
Multimodal
+18.7 difference
Command A+
Kimi K2.5
$2.5 / $10
$0.6 / $3
272 t/s
45 t/s
0.25s
2.38s
128K
256K
Pick Kimi K2.5 if you want the stronger benchmark profile. Command A+ only becomes the better choice if you want the stronger reasoning-first profile.
Kimi K2.5 is clearly ahead on the provisional aggregate, 64 to 32. 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 multimodal & grounded, where it averages 78.5 against 59.8. The single biggest benchmark swing on the page is MMMU-Pro, 63% to 78.5%.
Command A+ is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 3.3x on output cost alone. Command A+ is the reasoning model in the pair, while Kimi K2.5 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 K2.5 gives you the larger context window at 256K, compared with 128K for Command A+.
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 64 to 32. The biggest single separator in this matchup is MMMU-Pro, where the scores are 63% and 78.5%.
Kimi K2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 59.8. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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