How to Autostart gemma-4-E4B-it Offline on PC

The fastest way to get this model running locally is via Docker.

Please follow the instructions listed below to get started.

The loader auto-caches the model archive (several GBs included).

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🔐 Hash sum: 4dd286d3fc587b5232b78fd563542010 | 📅 Last update: 2026-06-24 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk: 150+ GB for high-context vector database storage GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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.

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