Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
68
MiMo-V2-Flash
62
Verified leaderboard positions: Kimi K2.5 #9 · MiMo-V2-Flash unranked
Pick Kimi K2.5 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+9.2 difference
Knowledge
+19.4 difference
Math
+2.0 difference
Kimi K2.5
MiMo-V2-Flash
$0.5 / $2.8
$0 / $0
45 t/s
129 t/s
2.38s
2.14s
256K
256K
Pick Kimi K2.5 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Kimi K2.5 is clearly ahead on the provisional aggregate, 68 to 62. 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 mathematics, where it averages 96.1 against 94.1. The single biggest benchmark swing on the page is GPQA, 87.6% to 83.7%. MiMo-V2-Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 is also the more expensive model on tokens at $0.50 input / $2.80 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. MiMo-V2-Flash 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 is ahead on BenchLM's provisional leaderboard, 68 to 62. The biggest single separator in this matchup is GPQA, where the scores are 87.6% and 83.7%.
MiMo-V2-Flash has the edge for knowledge tasks in this comparison, averaging 84.5 versus 65.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for coding in this comparison, averaging 73.4 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 94.1. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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