mlc-ai/xgrammar

Health v2 · maintenance only

Adoption not part of the score

1964 stars · 236 forks observed · 2026-10-18

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

XGrammar is an open-source library for efficient, flexible, and portable structured generation in LLM inference via constrained decoding. It guarantees structurally correct outputs (JSON, regex, context-free grammars) with near-zero overhead and integrates into engines like vLLM, SGLang, and TensorRT-LLM.

Use cases

• force an LLM to output valid JSON matching a schema
• constrain model outputs to a regex or context-free grammar
• reliable tool calling and function calling for LLMs
• add structured output support to a custom LLM inference engine
• guarantee 100% syntactically correct model generations
• generate structured outputs with low latency overhead

When to choose

• you need guaranteed-valid structured output from an LLM
• you want near-zero overhead constrained decoding at scale
• you need portability across platforms, languages, and inference engines
• you support general grammars beyond simple JSON schemas

When to avoid

• you only need unconstrained free-form text generation
• you want a full LLM serving stack rather than a structured generation library
• your use case is simple prompt-based formatting without hard guarantees

Facets

library · maturity active

llm-inference parser serialization sdk large-language-models machine-learning developer-tools python cpp cross-platform wasm constrained-decoding structured-output json-schema grammar ebnf tool-calling llm-engine-integration gpu javascript

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