Homebrew offers the quickest path to setting up this model locally.
Make sure to follow the instructions below.
All large files and heavy weights are downloaded automatically by the script.
The automated script takes care of everything, tailoring the setup to your specs.
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📄 Hash Value:
4080df4367635f79eed0e2344c409ae8 | 📆 Update: 2026-06-28
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Gemma-4-E4B-it is a state‑of‑the‑art language model engineered for high‑efficiency inference on edge devices. It incorporates 2 B parameters and a 4 K context window, allowing nuanced comprehension while preserving low latency. The architecture leverages advanced quantization techniques to achieve sub‑2 ms token generation on consumer hardware. Its design includes multi‑head attention and grouped‑query attention, delivering strong performance across benchmarks such as MMLU and GSM‑8K. The model also supports seamless integration with developer tools through its open‑source API.
| Parameters | 2 B |
| Context Length | 4 K tokens |
| Quantization | INT4 |
| Throughput | >2000 tokens/s on GPU |
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