Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
62
MiMo-V2.5
74
Pick MiMo-V2.5 if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
Agentic
+22.9 difference
Multimodal
+11.8 difference
GPT-5.4 nano
MiMo-V2.5
$0.2 / $1.25
$0.4 / $2
191 t/s
N/A
3.64s
N/A
400K
1M
Pick MiMo-V2.5 if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
MiMo-V2.5 is clearly ahead on the provisional aggregate, 74 to 62. 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 agentic, where it averages 65.8 against 42.9. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 46.3% to 65.8%.
MiMo-V2.5 is also the more expensive model on tokens at $0.40 input / $2.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. MiMo-V2.5 gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.
MiMo-V2.5 is ahead on BenchLM's provisional leaderboard, 74 to 62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 46.3% and 65.8%.
MiMo-V2.5 has the edge for agentic tasks in this comparison, averaging 65.8 versus 42.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
MiMo-V2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 77.9 versus 66.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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