Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Holo3-122B-A10B
78
MiMo-V2.5-Pro
82
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Agentic
+10.5 difference
Holo3-122B-A10B
MiMo-V2.5-Pro
$0.4 / $3
$1 / $3
N/A
N/A
N/A
N/A
64K
1M
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if agentic 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, 82 to 78. 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 Holo3-122B-A10B 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 gives you the larger context window at 1M, compared with 64K for Holo3-122B-A10B.
MiMo-V2.5-Pro is ahead on BenchLM's provisional leaderboard, 82 to 78.
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 68.4. MiMo-V2.5-Pro stays close enough that the answer can still flip depending on your workload.
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