Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
64
MiMo-V2-Omni
83
Verified leaderboard positions: Kimi K2.5 #11 · MiMo-V2-Omni unranked
Pick MiMo-V2-Omni if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+10.6 difference
Kimi K2.5
MiMo-V2-Omni
$0.6 / $3
N/A
45 t/s
N/A
2.38s
N/A
256K
262K
Pick MiMo-V2-Omni if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2-Omni is clearly ahead on the provisional aggregate, 83 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Omni's sharpest advantage is in coding, where it averages 74.8 against 64.2. The single biggest benchmark swing on the page is SWE-bench Verified, 76.8% to 74.8%.
MiMo-V2-Omni 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. MiMo-V2-Omni gives you the larger context window at 262K, compared with 256K for Kimi K2.5.
MiMo-V2-Omni is ahead on BenchLM's provisional leaderboard, 83 to 64. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 76.8% and 74.8%.
MiMo-V2-Omni has the edge for coding in this comparison, averaging 74.8 versus 64.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.