Update README.md

README.md

@@ -54,7 +54,7 @@ The model is quantized with nvidia-modelopt **v0.15.1**  <br>
 **Test Hardware:** H100 <br>
 
 ## Post Training Quantization
-This model was obtained by quantizing the weights and activations of Meta-Llama-3.1-8B to FP8 data type, ready for inference with TensorRT-LLM and vLLM. Only the weights and activations of the linear operators within transformers blocks are quantized. This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%. On H100, we achieved speedup
+This model was obtained by quantizing the weights and activations of Meta-Llama-3.1-8B to FP8 data type, ready for inference with TensorRT-LLM and vLLM. Only the weights and activations of the linear operators within transformers blocks are quantized. This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%. On H100, we achieved 1.3x speedup.
 
 ## Usage