Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 31B
66
MiMo-V2.5
74
Pick MiMo-V2.5 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you want the cheaper token bill.
Coding
+14.5 difference
Multimodal
+1.0 difference
Gemma 4 31B
MiMo-V2.5
$0 / $0
$0.4 / $2
N/A
N/A
N/A
N/A
256K
1M
Pick MiMo-V2.5 if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if you want the cheaper token bill.
MiMo-V2.5 is clearly ahead on the provisional aggregate, 74 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2.5's sharpest advantage is in coding, where it averages 56.1 against 41.6. The single biggest benchmark swing on the page is MMMU-Pro, 76.9% to 77.9%.
MiMo-V2.5 is also the more expensive model on tokens at $0.40 input / $2.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 31B. That is roughly Infinityx on output cost alone. MiMo-V2.5 gives you the larger context window at 1M, compared with 256K for Gemma 4 31B.
MiMo-V2.5 is ahead on BenchLM's provisional leaderboard, 74 to 66. The biggest single separator in this matchup is MMMU-Pro, where the scores are 76.9% and 77.9%.
MiMo-V2.5 has the edge for coding in this comparison, averaging 56.1 versus 41.6. Gemma 4 31B stays close enough that the answer can still flip depending on your workload.
MiMo-V2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 77.9 versus 76.9. 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.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.