Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.2
94
MiMo-V2-Flash
59
Verified leaderboard positions: GLM-5.2 #9 · MiMo-V2-Flash unranked
Pick GLM-5.2 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Coding
+11.3 difference
Knowledge
+17.3 difference
GLM-5.2
MiMo-V2-Flash
$1.4 / $4.4
$0 / $0
N/A
129 t/s
N/A
2.14s
1M
256K
Pick GLM-5.2 if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.2 is also the more expensive model on tokens at $1.40 input / $4.40 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. GLM-5.2 gives you the larger context window at 1M, compared with 256K for MiMo-V2-Flash.
GLM-5.2 is ahead on BenchLM's provisional leaderboard, 94 to 59. The biggest single separator in this matchup is GPQA, where the scores are 91.2% and 83.7%.
MiMo-V2-Flash has the edge for knowledge tasks in this comparison, averaging 84.5 versus 67.2. Inside this category, GPQA 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 62.1. GLM-5.2 stays close enough that the answer can still flip depending on your workload.
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