gemma-4-E4B-it

Docker offers the quickest path to setting up this model locally.

Simply follow the directions outlined below.

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The setup auto-streams the model assets (expect a multi-GB download).

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🛡️ Checksum: c99b44cda349c9b923410a0837d46ab1 — ⏰ Updated on: 2026-06-23 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: at least 32 GB in dual-channel mode for bandwidth 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.

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