gemma 4 31B it FP8 block Model Overview Model Architecture: google/gemma 4 31B it Input: Text / Image Output: Text Model Optimizations: Weight quantization: FP8 Activation quantization: FP8 Release Date: 2026 04 04 Version: 1.0 Model Developers: RedHatAI This model is a quantized version of google/gemma 4 31B it. It was evaluated on several tasks to assess its quality in comparison to the unquantized model. Model Optimizations This model was obtained by quantizing the weights and activations of google/gemma 4 31B it to FP8 data type, ready for inference with vLLM. This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%. Only the weights and activations of the linear operators within transformers blocks are quantized using LLM Compressor. Vision tower, embedding, and output head layers are kept in their original precision. Deployment Use with vLLM This model can be deployed using vLLM. For detailed instructions including multi GPU deployment, multimodal inference, thinking mode, function calling, and benchmarking, see the Gemma 4 vLLM usage guide. 1. Start the vLLM server: To enable thinking/rea…
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