Install gemma-4-31B-it-qat-w4a16-ct on AMD/Nvidia GPU

The most rapid route to a local installation of this model is through Docker.

Simply follow the directions outlined below.

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The installer automatically pulls the model (could be multiple GBs).

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📘 Build Hash: b569b74def5d531ee28c4010c66b30e7 • 🗓 2026-06-23 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: CUDA Compute Capability 8.0+ required for flash-attention

The Gemma-4-31B-it-qat-w4a16-ct is a large language model designed for instruction following and conversational tasks. It leverages 31 billion parameters to achieve a balance between accuracy and computational efficiency. The model employs QAT (quantized aware training) combined with a w4a16 format, enabling reduced memory footprint while preserving performance. Its CT architecture incorporates advanced attention mechanisms that improve context retention and response relevance. The following table summarizes key technical attributes.

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