gemma-4-E4B-it with Native FP4 Dummy Proof Guide

gemma-4-E4B-it with Native FP4 Dummy Proof Guide

To install this model locally in the shortest time, opt for a direct curl execution.

Check out the detailed setup guide below to begin.

The engine will automatically fetch large dependencies in the background.

The deployment tool scans your environment and chooses the ideal parameters.

🔗 SHA sum: 62e167ca0bae053555eefabfe22bfb4f | Updated: 2026-06-23



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space:70 GB free space for full FP16 weights storage
  • 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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