qwenlm/qwen3

Qwen3 is a family of large language models, the kind of AI system that generates text in response to prompts, developed by the Qwen team at Alibaba Cloud. A large language model is the same general type of system that powers chat assistants and code helpers: you give it a question or instruction and it produces a written answer. This repository hosts the documentation and pointers to the actual model weight files, which are published on Hugging Face and ModelScope. The README describes two main flavors. An instruct version is tuned for direct chat and following instructions. A thinking version is tuned for reasoning-heavy tasks such as math, logic, science, and code, and works through problems in more deliberate steps before answering. Both come in several sizes, from small models in the single-digit billions of parameters to large ones in the hundreds of billions, with some built as Mixture-of-Experts designs that activate only part of the network per request. Recent updates extend the context window to 256K tokens and, for some variants, up to 1 million tokens. Someone would use Qwen3 to build a chatbot, a coding assistant, a translator, or an agent that calls external tools, any application that needs to generate or reason over text, especially when they want an open-weight model they can run themselves rather than calling a closed API. The README highlights support for over 100 languages and dialects. The repository is primarily documentation in a Python project layout, pointing to inference with Hugging Face Transformers and to local or server deployment via llama.cpp, Ollama, LM Studio, SGLang, vLLM, and TGI.