A fast model can still spend time waiting for CPU-side grammar checks. The useful insight is that most token-validity decisions depend only on a local grammar state, so they can be cached before generation rather than recomputed for every token.
Key Findings
- Separating cacheable checks from stack-dependent checks preserves recursive grammar support while reducing runtime work.
- Context expansion and persistent stacks handle the remaining cases and enable efficient branching and rollback.
- The authors report up to 100× faster mask generation than existing methods in their evaluation. Overlapping grammar work with GPU execution makes structured output overhead nearly disappear in tested serving configurations; this is not a universal application speedup.
Who Should Read It
Useful for inference engineers serving tool calls, nested JSON, or domain-specific output languages. It explains where format enforcement belongs in a serving pipeline. Grammar compliance does not establish that an answer is factually correct or that a proposed tool action is appropriate; those need separate checks.