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

Use the instructions provided below to complete the setup.

The loader auto-caches the model archive (several GBs included).

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

💾 File hash: e51872dc05964bae2133594b13bae1f9 (Update date: 2026-06-26) Verify Processor: high single-core performance needed for token latency RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The gemma-4-E4B-it model represents a significant advancement in open‑source language models, combining massive scale with efficient inference capabilities. It features 2.5 trillion parameters, enabling it to understand and generate highly nuanced text across a wide range of domains. With a context window of 128K tokens, the model can maintain coherence in long‑form conversations and documents. A dedicated

Benchmarks show that gemma-4-E4B-it outperforms previous models on reasoning, coding, and multilingual tasks while consuming less computational resources.

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