Deploying this model locally is quickest when done via Docker.

Please follow the instructions listed below to get started.

The setup auto-downloads all needed files (several GBs).

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

🔐 Hash sum: d4b0f0ecc4c0e96b6bc87b0d688d0163 | 📅 Last update: 2026-06-23 Verify Processor: 6-core 3.5 GHz minimum required RAM: at least 32 GB in dual-channel mode for bandwidth Disk: high-speed SSD 120 GB to cache model layers Graphics: 12 GB VRAM minimum required for basic quantization

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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