sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
A compact implementation of SGLang, designed to demystify the complexities of modern LLM serving systems.
SGLang is a high-performance serving framework for large language models and multimodal models.
A framework for few-shot evaluation of language models.
LLM inference in C/C++
Qwen3.6 is the large language model series developed by Qwen team, Alibaba Group.
A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling.
slime is an LLM post-training framework for RL Scaling.
1 capture since 2026-05-25