Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemma 4 E4B
~47
1/8 categoriesGPT-5.4 nano
58
Winner · 3/8 categoriesGemma 4 E4B· GPT-5.4 nano
Pick GPT-5.4 nano if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
GPT-5.4 nano is clearly ahead on the aggregate, 58 to 47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 nano's sharpest advantage is in multimodal & grounded, where it averages 66.1 against 52.6. The single biggest benchmark swing on the page is GPQA, 58.6% to 82.8%. Gemma 4 E4B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 nano is also the more expensive model on tokens at $0.20 input / $1.25 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 E4B. That is roughly Infinityx on output cost alone. GPT-5.4 nano gives you the larger context window at 400K, compared with 128K for Gemma 4 E4B.
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 | GPT-5.4 nano |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 46.3% |
| OSWorld-Verified | — | 39% |
| MCP Atlas | — | 56.1% |
| Toolathlon | — | 35.5% |
| Tau2-Telecom | — | 92.5% |
| CodingGPT-5.4 nano wins | ||
| LiveCodeBench | 52% | — |
| SWE-bench Pro | — | 52.4% |
| Multimodal & GroundedGPT-5.4 nano wins | ||
| MMMU-Pro | 52.6% | 66.1% |
| MMMU-Pro w/ Python | — | 69.5% |
| ReasoningGPT-5.4 nano wins | ||
| BBH | 33.1% | — |
| MRCRv2 | 25.4% | 38.7% |
| MRCR v2 64K-128K | — | 44.2% |
| MRCR v2 128K-256K | — | 33.1% |
| Graphwalks BFS 128K | — | 73.4% |
| Graphwalks Parents 128K | — | 50.8% |
| KnowledgeGemma 4 E4B wins | ||
| GPQA | 58.6% | 82.8% |
| MMLU-Pro | 69.4% | — |
| HLE | — | 37.7% |
| HLE w/o tools | — | 24.3% |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| Coming soon | ||
GPT-5.4 nano is ahead overall, 58 to 47. The biggest single separator in this matchup is GPQA, where the scores are 58.6% and 82.8%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 53.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.4 nano has the edge for coding in this comparison, averaging 52.4 versus 52. Gemma 4 E4B stays close enough that the answer can still flip depending on your workload.
GPT-5.4 nano has the edge for reasoning in this comparison, averaging 38.7 versus 25.4. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.4 nano has the edge for multimodal and grounded tasks in this comparison, averaging 66.1 versus 52.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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