xgrammar 0.2.2

Efficient, Flexible and Portable Structured Generation

Efficient, Flexible and Portable Structured Generation

Get Started | Documentation | Blogpost | Technical Report

News

• [2026/5] XGrammar-2 has been released! Check out our blog for more information.
• [2025/12] XGrammar has been officially integrated into Mirai
• [2025/09] XGrammar has been officially integrated into OpenVINO GenAI
• [2025/02] XGrammar has been officially integrated into Modular's MAX
• [2025/01] XGrammar has been officially integrated into TensorRT-LLM.
• [2024/12] XGrammar has been officially integrated into vLLM.
• [2024/12] We presented research talks on XGrammar at CMU, UC Berkeley, MIT, THU, SJTU, Ant Group, LMSys, Qingke AI, Camel AI. The slides can be found here.
• [2024/11] XGrammar has been officially integrated into SGLang.
• [2024/11] XGrammar has been officially integrated into MLC-LLM.
• [2024/11] We officially released XGrammar v0.1.0!

Overview

XGrammar is an open-source library for efficient, flexible, and portable structured generation.

It leverages constrained decoding to ensure 100% structural correctness of the output. It supports general context-free grammar to enable a broad range of structures, including JSON, regex, custom context-free grammar, etc.

XGrammar uses careful optimizations to achieve extremely low overhead in structured generation. It has achieved near-zero overhead in JSON generation, making it one of the fastest structured generation engines available.

XGrammar features universal deployment. It supports:

• Platforms: Linux, macOS, Windows
• Hardware: CPU, NVIDIA GPU, AMD GPU, Apple Silicon, TPU, etc.
• Languages: Python, C++, JavaScript, and Swift APIs
• Models: Qwen, Llama, DeepSeek, Phi, Gemma, etc.

XGrammar is very easy to integrate with LLM inference engines. It is the default structured generation backend for most LLM inference engines, including vLLM, SGLang, TensorRT-LLM, and MLC-LLM, as well as many other companies. You can also try out their structured generation modes!

Get Started

Install XGrammar:

pip install xgrammar

For use with MPS on Apple Silicon, install with:

pip install "xgrammar[metal]"

Import XGrammar:

import xgrammar as xgr

Please visit our documentation to get started with XGrammar.

• Installation
• Quick start

Third-Party Bindings

• Rust: xgrammar-rs — Community Rust bindings for XGrammar.

Collaborators

XGrammar has been widely adopted in industry, open-source projects, and academia. Our collaborators include:

                      WebLLM  

Citation

If you find XGrammar useful in your research, please consider citing our papers:

@article{dong2024xgrammar,
  title={Xgrammar: Flexible and efficient structured generation engine for large language models},
  author={Dong, Yixin and Ruan, Charlie F and Cai, Yaxing and Lai, Ruihang and Xu, Ziyi and Zhao, Yilong and Chen, Tianqi},
  journal={Proceedings of Machine Learning and Systems 7},
  year={2024}
}
@inproceedings{10.1145/3786335.3813124,
  author = {Li, Linzhang and Dong, Yixin and Wang, Guanjie and Xu, Ziyi and Jiang, Alexander and Chen, Tianqi},
  title = {XGrammar-2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs},
  year = {2026},
  isbn = {9798400724152},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3786335.3813124},
  booktitle = {Proceedings of the ACM Conference on AI and Agentic Systems},
  pages = {1009--1022},
  numpages = {14}
}