FastDeploy is a high-performance inference and deployment toolkit for large language models and vision-language models built on PaddlePaddle.
The toolkit addresses the challenge of efficiently deploying LLMs and VLMs in production environments. It provides production-ready deployment solutions with core technical features including support for multiple model architectures, quantization methods, and hardware platforms. The approach centers on optimizing inference performance across different hardware configurations while maintaining ease of use for practitioners deploying these models at scale.
Organizations should adopt FastDeploy if they are deploying PaddlePaddle-based models or models compatible with the PaddlePaddle ecosystem, particularly when targeting multiple hardware platforms. The toolkit suits projects requiring production-grade inference serving with emphasis on performance optimization. It is especially relevant for teams working with ERNIE models and other models within the PaddlePaddle ecosystem, as well as those seeking HuggingFace ecosystem model compatibility.
The project shows active development with regular feature releases introducing support for new model architectures, enhanced quantization methods, and performance improvements across hardware platforms. Development includes substantial bug fixes and optimizations alongside new model support additions. The toolkit maintains broad hardware platform support with ongoing enhancements for specialized accelerators and inference optimization techniques.
