Deploy gemma-4-26B-A4B-it-QAT-MLX-4bit Windows 11 Zero Config Local Guide
Running this model locally is fastest when deployed through a PowerShell script.
Just follow the guidelines provided below.
The installer automatically pulls the model (could be multiple GBs).
The configuration wizard runs silently to set up the model for peak performance.
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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