Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 nano
27
MiMo-V2-Flash
61
Pick MiMo-V2-Flash if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+34.2 difference
GPT-4.1 nano
MiMo-V2-Flash
$0.1 / $0.4
$0 / $0
181 t/s
129 t/s
0.63s
2.14s
1M
256K
Pick MiMo-V2-Flash if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2-Flash is clearly ahead on the provisional aggregate, 61 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Flash's sharpest advantage is in knowledge, where it averages 84.5 against 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 83.7%.
GPT-4.1 nano is also the more expensive model on tokens at $0.10 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. MiMo-V2-Flash is the reasoning model in the pair, while GPT-4.1 nano 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. GPT-4.1 nano gives you the larger context window at 1M, compared with 256K for MiMo-V2-Flash.
MiMo-V2-Flash is ahead on BenchLM's provisional leaderboard, 61 to 27. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 83.7%.
MiMo-V2-Flash has the edge for knowledge tasks in this comparison, averaging 84.5 versus 50.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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