Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
Winner · 3/8 categoriesGLM-4.5-Air
38
1/8 categoriesGemma 4 E4B· GLM-4.5-Air
Pick Gemma 4 E4B if you want the stronger benchmark profile. GLM-4.5-Air only becomes the better choice if reasoning is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 E4B is clearly ahead on the aggregate, 47 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 E4B's sharpest advantage is in knowledge, where it averages 65.6 against 31. The single biggest benchmark swing on the page is LiveCodeBench, 52% to 15%. GLM-4.5-Air does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
Gemma 4 E4B is the reasoning model in the pair, while GLM-4.5-Air 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.
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 E4B | GLM-4.5-Air |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 28% |
| BrowseComp | — | 37% |
| Claw-Eval | — | 42.3% |
| CodingGemma 4 E4B wins | ||
| LiveCodeBench | 52% | 15% |
| HumanEval | — | 27% |
| SWE-bench Verified | — | 15% |
| SWE-bench Pro | — | 14% |
| SWE-Rebench | — | 38.3% |
| Multimodal & GroundedGemma 4 E4B wins | ||
| MMMU-Pro | 52.6% | 36% |
| ReasoningGLM-4.5-Air wins | ||
| BBH | 33.1% | 63% |
| MRCRv2 | 25.4% | 51% |
| MuSR | — | 31% |
| LongBench v2 | — | 47% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | 34% |
| MMLU-Pro | 69.4% | 51% |
| MMLU | — | 35% |
| SuperGPQA | — | 32% |
| HLE | — | 4% |
| FrontierScience | — | 37% |
| SimpleQA | — | 33% |
| Instruction Following | ||
| IFEval | — | 68% |
| Multilingual | ||
| MGSM | — | 63% |
| MMLU-ProX | — | 57% |
| Mathematics | ||
| AIME 2023 | — | 35% |
| AIME 2024 | — | 37% |
| AIME 2025 | — | 36% |
| HMMT Feb 2023 | — | 31% |
| HMMT Feb 2024 | — | 33% |
| HMMT Feb 2025 | — | 32% |
| BRUMO 2025 | — | 34% |
| MATH-500 | — | 57% |
Gemma 4 E4B is ahead overall, 47 to 38. The biggest single separator in this matchup is LiveCodeBench, where the scores are 52% and 15%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 31. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for coding in this comparison, averaging 52 versus 22.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for reasoning in this comparison, averaging 44.1 versus 25.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
Gemma 4 E4B has the edge for multimodal and grounded tasks in this comparison, averaging 52.6 versus 36. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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