Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
82
MiMo-V2.5-Pro
85
Verified leaderboard positions: GLM-5.1 #29 · MiMo-V2.5-Pro unranked
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if knowledge is the priority.
Agentic
+3.1 difference
Coding
+3.7 difference
Knowledge
+4.3 difference
GLM-5.1
MiMo-V2.5-Pro
$1.4 / $4.4
$null / $null
N/A
N/A
N/A
N/A
203K
1M
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if knowledge is the priority.
MiMo-V2.5-Pro has the cleaner provisional overall profile here, landing at 85 versus 82. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
MiMo-V2.5-Pro's sharpest advantage is in agentic, where it averages 68.4 against 65.3. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 68.4%. GLM-5.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5-Pro gives you the larger context window at 1M, compared with 203K for GLM-5.1.
MiMo-V2.5-Pro is ahead on BenchLM's provisional leaderboard, 85 to 82. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 68.4%.
GLM-5.1 has the edge for knowledge tasks in this comparison, averaging 52.3 versus 48. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.
GLM-5.1 has the edge for coding in this comparison, averaging 60.9 versus 57.2. Inside this category, AA-SciCode 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 65.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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