Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
84
MiMo-V2.5
74
Pick GLM-5.1 if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Agentic
+0.5 difference
Coding
+4.8 difference
GLM-5.1
MiMo-V2.5
$1.4 / $4.4
$0.4 / $2
N/A
N/A
N/A
N/A
203K
1M
Pick GLM-5.1 if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if agentic is the priority or you want the cheaper token bill.
GLM-5.1 is clearly ahead on the provisional aggregate, 84 to 74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in coding, where it averages 60.9 against 56.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 65.8%. MiMo-V2.5 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
GLM-5.1 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.40 input / $2.00 output per 1M tokens for MiMo-V2.5. That is roughly 2.2x on output cost alone. MiMo-V2.5 gives you the larger context window at 1M, compared with 203K for GLM-5.1.
GLM-5.1 is ahead on BenchLM's provisional leaderboard, 84 to 74. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 65.8%.
GLM-5.1 has the edge for coding in this comparison, averaging 60.9 versus 56.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiMo-V2.5 has the edge for agentic tasks in this comparison, averaging 65.8 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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