MLC-LLM

DiffSynth-Studio is an open-source Diffusion model engine developed and maintained by the ModelScope Community, focusing on image and video generation. It supports mainstream models like FLUX, Wan, and Qwen-Image, offering efficient memory management and flexible training frameworks. Key features include VRAM optimization, low-memory inference, LoRA/ControlNet training, and innovative techniques like EliGen and Nexus-Gen for pushing generative model boundaries.

SGLang is a high-performance serving framework for large language models (LLMs) and vision-language models, designed for low-latency and high-throughput inference across single GPUs to large distributed clusters. Key features include RadixAttention for prefix caching, zero-overhead batch scheduling, prefill-decode disaggregation, speculative decoding, continuous batching, paged attention, tensor/pipeline/expert/data parallelism, structured outputs, chunked prefill, and quantization (FP4/FP8/INT4/AWQ/GPTQ). It supports a wide range of models like Llama, Qwen, DeepSeek, and hardware from NVIDIA, AMD, Intel, TPUs, with an intuitive frontend for LLM applications.

stable-diffusion.cpp is a pure C/C++ implementation for diffusion model inference, based on ggml, supporting models like Stable Diffusion (SD1.x, SD2.x, SDXL), Flux, Wan, Qwen Image, Z-Image, and more. It's lightweight with no external dependencies, supports backends like CPU, CUDA, Vulkan, Metal, and features like LoRA, ControlNet, LCM for efficient local image generation on platforms including Linux, Mac, Windows, and Android.