📄 中文摘要
在AI工具的选择中，推理引擎的选择被认为是最重要的决策之一。许多团队在这一选择上犯了错误，导致整体AI架构的效率低下。本文对六种流行的推理引擎进行了比较，分别是vLLM、TGI、TensorRT-LLM、SGLang、llama.cpp和Ollama。每种引擎都有其独特的优势和适用场景，选择合适的推理引擎可以显著提升模型的性能和响应速度。对工程师而言，理解这些工具的差异和特点是构建高效AI系统的关键。
大型语言模型推理引擎对决：vLLM vs TGI vs TensorRT-LLM vs SGLang vs llama.cpp vs Ollama
📄 English Summary
The Great LLM Inference Engine Showdown: vLLM vs TGI vs TensorRT-LLM vs SGLang vs llama.cpp vs Ollama
Choosing the right inference engine is one of the most critical decisions in an AI stack, yet many teams make mistakes in this area, leading to inefficiencies. This issue compares six popular inference engines: vLLM, TGI, TensorRT-LLM, SGLang, llama.cpp, and Ollama. Each engine has its unique strengths and use cases, and selecting the appropriate one can significantly enhance model performance and response times. For engineers, understanding the differences and characteristics of these tools is crucial for building efficient AI systems.