Zero-Click Run gemma-4-26B-A4B-it-QAT-MLX-4bit PC with NPU with 1M Context
If you want the fastest local installation for this model, use Docker.
Refer to the instructions below to proceed.
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.
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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