gemma-4-E4B-it 2026/2027 Tutorial

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

Review and follow the instructions below.

The installer automatically pulls the model (could be multiple GBs).

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

📤 Release Hash: cdf663177f30cbc91cf2da50a7c389fa • 📅 Date: 2026-06-23



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Storage:100 GB free space for HuggingFace cache folder
  • 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

https://oceanica.org.br/category/examples/

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