FastDeploy and llm-deploy
PaddlePaddle/FastDeploy is an ecosystem sibling to lix19937/llm-deploy, as the former is a high-performance deployment toolkit for inference, which could be leveraged as a backend for the latter, an AI infrastructure tool for LLM inference that integrates various runtimes like TensorRT-LLM and vLLM.
About FastDeploy
PaddlePaddle/FastDeploy
High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle
This tool helps machine learning engineers and AI researchers deploy large language models (LLMs) and vision-language models (VLMs) efficiently. It takes trained PaddlePaddle-based models and optimizes them for high-performance inference, outputting a production-ready deployment solution. You would use this if you need to serve advanced AI models like ERNIE-4.5 or PaddleOCR-VL in real-world applications with speed and reliability.
About llm-deploy
lix19937/llm-deploy
AI Infra LLM infer/ tensorrt-llm/ vllm
This project helps AI infrastructure engineers optimize large language model (LLM) inference. It provides techniques and frameworks to accelerate the processing of LLMs, reducing the time it takes to get responses (latency) and increasing the number of requests handled per second (throughput). The end-users are engineers responsible for deploying and maintaining LLM-powered applications in production environments.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work