gemma-4-E4B-it with Native FP4 Offline Setup

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

Please follow the instructions listed below to get started.

Hands-free setup: the system self-downloads the heavy model files.

There is no manual tuning required; the builder will automatically deploy the best matching configuration.

📤 Release Hash: df62986acf53f3b8c7c2156be17371c9 • 📅 Date: 2026-06-26 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: enough space for background apps and OS overhead Storage:100 GB free space for HuggingFace cache folder GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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.

• Script downloading optimized tokenizers designed specifically for complex localized languages translation suites
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