PaddleNLP is a large language model development toolkit built on the PaddlePaddle deep-learning framework. It supports efficient LLM training, lossless compression, and high-performance inference across multiple hardware platforms, with an emphasis on ease of use and high performance for production applications. It supports hardware including NVIDIA GPUs, Kunlun XPUs, Ascend NPUs, Enflame GCUs, and Hygon DCUs, with interfaces designed to reduce the engineering cost of moving between accelerators.

The README highlights support for model families such as Qwen3 and DeepSeek-R1, multiple distributed-training strategies, FlashMask-based memory optimization, broad model-parameter support across LLaMA, Baichuan, Bloom, ChatGLM, Gemma, Mistral, OPT, and Qwen families, and 4D parallelism plus operator optimizations for major LLM architectures.