Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 31B
73
1/8 categoriesGLM-5 (Reasoning)
82
Winner · 3/8 categoriesGemma 4 31B· GLM-5 (Reasoning)
Pick GLM-5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 31B only becomes the better choice if coding is the priority or you need the larger 256K context window.
GLM-5 (Reasoning) is clearly ahead on the aggregate, 82 to 73. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5 (Reasoning)'s sharpest advantage is in reasoning, where it averages 90 against 66.4. The single biggest benchmark swing on the page is BBH, 74.4% to 91%. Gemma 4 31B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B gives you the larger context window at 256K, compared with 200K for GLM-5 (Reasoning).
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Gemma 4 31B | GLM-5 (Reasoning) |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 81% |
| BrowseComp | — | 80% |
| OSWorld-Verified | — | 74% |
| CodingGemma 4 31B wins | ||
| LiveCodeBench | 80% | — |
| HumanEval | — | 88% |
| SWE-bench Verified | — | 62% |
| Multimodal & GroundedGLM-5 (Reasoning) wins | ||
| MMMU-Pro | 76.9% | 74% |
| OfficeQA Pro | — | 84% |
| ReasoningGLM-5 (Reasoning) wins | ||
| BBH | 74.4% | 91% |
| MRCRv2 | 66.4% | — |
| MuSR | — | 90% |
| KnowledgeGLM-5 (Reasoning) wins | ||
| GPQA | 84.3% | 94% |
| MMLU-Pro | 85.2% | 81% |
| HLE | 26.5% | 29% |
| HLE w/o tools | 19.5% | — |
| MMLU | — | 96% |
| SuperGPQA | — | 92% |
| FrontierScience | — | 83% |
| SimpleQA | — | 92% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| MGSM | — | 89% |
| Mathematics | ||
| AIME 2023 | — | 98% |
| AIME 2024 | — | 99% |
| AIME 2025 | — | 98% |
| HMMT Feb 2023 | — | 94% |
| HMMT Feb 2024 | — | 96% |
| HMMT Feb 2025 | — | 95% |
| BRUMO 2025 | — | 96% |
| MATH-500 | — | 92% |
GLM-5 (Reasoning) is ahead overall, 82 to 73. The biggest single separator in this matchup is BBH, where the scores are 74.4% and 91%.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 73.7 versus 61.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 31B has the edge for coding in this comparison, averaging 80 versus 62. GLM-5 (Reasoning) stays close enough that the answer can still flip depending on your workload.
GLM-5 (Reasoning) has the edge for reasoning in this comparison, averaging 90 versus 66.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 76.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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