Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
43
MiMo-V2.5-Pro
88
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+15.4 difference
DeepSeek V4 Pro Base
MiMo-V2.5-Pro
$null / $null
$null / $null
N/A
N/A
N/A
N/A
1M
1M
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2.5-Pro is clearly ahead on the provisional aggregate, 88 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5-Pro is the reasoning model in the pair, while DeepSeek V4 Pro Base 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-V2.5-Pro is ahead on BenchLM's provisional leaderboard, 88 to 43.
DeepSeek V4 Pro Base has the edge for knowledge tasks in this comparison, averaging 63.4 versus 48. MiMo-V2.5-Pro stays close enough that the answer can still flip depending on your workload.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.