Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
83
MiMo-V2.5-Pro
82
Pick GPT-5.2 if you want the stronger benchmark profile. MiMo-V2.5-Pro only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Agentic
+13.2 difference
Coding
+7.5 difference
Knowledge
+44.4 difference
GPT-5.2
MiMo-V2.5-Pro
$2 / $8
$1 / $3
73 t/s
N/A
130.34s
N/A
400K
1M
Pick GPT-5.2 if you want the stronger benchmark profile. MiMo-V2.5-Pro only becomes the better choice if agentic is the priority or you want the cheaper token bill.
GPT-5.2 finishes one point ahead on BenchLM's provisional leaderboard, 83 to 82. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 48. The single biggest benchmark swing on the page is SWE-bench Pro, 55.6% to 57.2%. MiMo-V2.5-Pro does hit back in agentic, 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 $2.00 input / $8.00 output per 1M tokens, versus $1.00 input / $3.00 output per 1M tokens for MiMo-V2.5-Pro. That is roughly 2.7x on output cost alone. MiMo-V2.5-Pro gives you the larger context window at 1M, compared with 400K for GPT-5.2.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 83 to 82. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 55.6% and 57.2%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 48. MiMo-V2.5-Pro stays close enough that the answer can still flip depending on your workload.
GPT-5.2 has the edge for coding in this comparison, averaging 64.7 versus 57.2. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiMo-V2.5-Pro has the edge for agentic tasks in this comparison, averaging 68.4 versus 55.2. GPT-5.2 stays close enough that the answer can still flip depending on your workload.
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