Launch gemma-4-26B-A4B-it-QAT-MLX-4bit Locally via LM Studio One-Click Setup Direct EXE Setup

Using Docker is the absolute quickest way to install this model on your local machine.

Make sure to follow the instructions below.

Otherwise, if you want to avoid container setups, just proceed with the basic instructions provided below.

🔒 Hash checksum: d03ae1afd4b5fb617603828ce1e11c72 • 📆 Last updated: 2026-06-25 Verify Processor: 6-core 3.5 GHz minimum required RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: required: fast PCIe 4.0 drive for instant boots 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.

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