Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 26B A4B
64
2/8 categoriesGLM-4.7
74
Winner · 2/8 categoriesGemma 4 26B A4B· GLM-4.7
Pick GLM-4.7 if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if coding is the priority or you need the larger 256K context window.
GLM-4.7 is clearly ahead on the aggregate, 74 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7's sharpest advantage is in reasoning, where it averages 78.9 against 44.1. The single biggest benchmark swing on the page is MRCRv2, 44.1% to 78%. Gemma 4 26B A4B does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemma 4 26B A4B gives you the larger context window at 256K, compared with 200K for GLM-4.7.
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 26B A4B | GLM-4.7 |
|---|---|---|
| Agentic | ||
| OSWorld-Verified | — | 61% |
| VITA-Bench | — | 15.5% |
| CodingGemma 4 26B A4B wins | ||
| LiveCodeBench | 77.1% | 84.9% |
| HumanEval | — | 94.2% |
| SWE-bench Verified | — | 73.8% |
| SWE-bench Pro | — | 51% |
| Multimodal & GroundedGemma 4 26B A4B wins | ||
| MMMU-Pro | 73.8% | 66% |
| OfficeQA Pro | — | 76% |
| ReasoningGLM-4.7 wins | ||
| BBH | 64.8% | 84% |
| MRCRv2 | 44.1% | 78% |
| MuSR | — | 80% |
| LongBench v2 | — | 79% |
| KnowledgeGLM-4.7 wins | ||
| GPQA | 82.3% | 85.7% |
| MMLU-Pro | 82.6% | 84.3% |
| HLE | 17.2% | — |
| HLE w/o tools | 8.7% | — |
| MMLU | — | 86% |
| SuperGPQA | — | 82% |
| FrontierScience | — | 72% |
| SimpleQA | — | 46% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| MGSM | — | 94% |
| MMLU-ProX | — | 78% |
| Mathematics | ||
| AIME 2023 | — | 86% |
| AIME 2024 | — | 88% |
| AIME 2025 | — | 95.7% |
| HMMT Feb 2023 | — | 82% |
| HMMT Feb 2025 | — | 97.1% |
| BRUMO 2025 | — | 85% |
GLM-4.7 is ahead overall, 74 to 64. The biggest single separator in this matchup is MRCRv2, where the scores are 44.1% and 78%.
GLM-4.7 has the edge for knowledge tasks in this comparison, averaging 74.8 versus 56.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for coding in this comparison, averaging 77.1 versus 69.3. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for reasoning in this comparison, averaging 78.9 versus 44.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Gemma 4 26B A4B has the edge for multimodal and grounded tasks in this comparison, averaging 73.8 versus 70.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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