Setup gemma-4-E4B-it on Your PC Offline Setup

Running this model locally is fastest when deployed through a PowerShell script.

Follow the sequence of steps detailed below.

1-click setup: the app automatically fetches the large weight files.

You don’t need to tweak anything; the installer picks the highest performing setup.

📊 File Hash: 37a88d46953649862564b8c15d118976 — Last update: 2026-07-06



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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.

Parameters2 B
Context Length4 K tokens
QuantizationINT4
Throughput>2000 tokens/s on GPU
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