XGrammar
Fast structured generation engine for grammar-constrained LLM decoding.
About
XGrammar is an open-source library for efficient structured generation, enforcing JSON schemas, regexes, and context-free grammars during decoding with near-zero overhead. Its adaptive token-mask caching and persistent execution stack made it the default structured-output backend in vLLM, SGLang, TensorRT-LLM, and MLC-LLM, replacing the older Outlines library in those engines.
It ships Python, C++, JavaScript, and Swift APIs and runs on CPU, NVIDIA and AMD GPUs, Apple Silicon, and TPUs. Independent analysis has flagged edge cases where it can emit under-constrained outputs against tricky JSON Schema test suites, so teams with strict compliance needs should still validate outputs rather than treat constraints as a guarantee.
What it can do
- Grammar-constrained decoding with near-zero overhead
- JSON Schema, regex, and CFG support
- Default backend in vLLM, SGLang, TensorRT-LLM
- Python, C++, JavaScript, Swift APIs
- CPU, GPU, Apple Silicon, TPU deployment
Setup
pip install xgrammar, then use it standalone or enable it as the structured-output backend in vLLM or SGLang.
Prerequisites
An LLM inference setup; familiarity with JSON Schema or grammar formats for defining constraints.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 79; Trending score 84/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.