Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
79
MiMo-V2-Flash
59
Pick GPT-5.2 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.
Coding
+8.7 difference
Knowledge
+7.9 difference
GPT-5.2
MiMo-V2-Flash
$1.75 / $14
$0 / $0
73 t/s
129 t/s
130.34s
2.14s
400K
256K
Pick GPT-5.2 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.2 is clearly ahead on the provisional aggregate, 79 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 84.5. The single biggest benchmark swing on the page is GPQA, 92.4% to 83.7%. MiMo-V2-Flash does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 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. GPT-5.2 gives you the larger context window at 400K, compared with 256K for MiMo-V2-Flash.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 59. The biggest single separator in this matchup is GPQA, where the scores are 92.4% and 83.7%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 84.5. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
MiMo-V2-Flash has the edge for coding in this comparison, averaging 73.4 versus 64.7. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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