Hands-on Large Language Model Inference Optimization: Systematic Evaluation and Comparative Analysis of Four Serving Frameworks

Introduction / Main Post: Hands-on Large Language Model Inference Optimization: Systematic Evaluation and Comparative Analysis of Four Serving Frameworks

This article provides an in-depth analysis of an open-source evaluation project targeting the Mistral-7B-Instruct-v0.3 model. From three dimensions—latency, throughput, and GPU efficiency—it conducts comparative tests on four deployment schemes: Hugging Face baseline, vLLM BF16, vLLM prefix caching, and vLLM AWQ INT4 quantization, and offers a directly runnable web demo environment.