Update README.md

README.md

@@ -35,7 +35,7 @@ It was evaluated on a several tasks to assess the its quality in comparison to t
 ### Model Optimizations
 
 This model was obtained by quantizing the weights and activations of [DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B) to FP4 data type, ready for inference with vLLM>=0.9.1
-This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 25%.
+This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%.
 
 Only the weights of the linear operators within transformers blocks are quantized using [LLM Compressor](https://github.com/vllm-project/llm-compressor).