GLM-5 vs MiMo-V2-Pro
Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verdict
MiMo-V2-Pro leads for most workloads.
Based on BenchLM composite scores, July 2026.
GLM-5
63
MiMo-V2-Pro
73
Verified leaderboard positions: GLM-5 #18 · MiMo-V2-Pro unranked
Pick MiMo-V2-Pro if you want the stronger benchmark profile. GLM-5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Category Radar
Head-to-Head by Category
Category Breakdown
| Benchmark | GLM-5 | Δ | MiMo-V2-Pro |
|---|---|---|---|
| Coding | 63.3 | → 14.7 | 78.0 |
| Agentic | 56.2 | — | — |
| Reasoning | 60.8 | — | — |
| Knowledge | 66.6 | — | — |
| Math | 56.3 | — | — |
| Multilingual | 83.1 | — | — |
| Inst. Following | 92.6 | — | — |
Operational Comparison
GLM-5
MiMo-V2-Pro
$1 / $3.2
N/A
74 t/s
N/A
1.64s
N/A
200K
1M
Quick Verdict
Pick MiMo-V2-Pro if you want the stronger benchmark profile. GLM-5 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2-Pro is clearly ahead on the provisional aggregate, 73 to 63. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Pro's sharpest advantage is in coding, where it averages 78 against 63.3. The single biggest benchmark swing on the page is SWE-bench Verified, 77.8% to 78%.
MiMo-V2-Pro is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. MiMo-V2-Pro gives you the larger context window at 1M, compared with 200K for GLM-5.
Benchmark Deep Dive
Frequently Asked Questions (2)
Which is better, GLM-5 or MiMo-V2-Pro?
MiMo-V2-Pro is ahead on BenchLM's provisional leaderboard, 73 to 63. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 77.8% and 78%.
Which is better for coding, GLM-5 or MiMo-V2-Pro?
MiMo-V2-Pro has the edge for coding in this comparison, averaging 78 versus 63.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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