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llama.cpp fixes grammar rejection for long tokens
llama.cpp Releaseshigh confidence
Why it matters
- →Fixes silent failures in JSON/list formatting for models with large vocabularies like GLM-4.7.
- →Improves grammar sampling speed by replacing recursion with an iterative stack approach.
- →Ensures structural constraints work reliably across extended token sets without arbitrary limits.
llama.cpp has released a patch addressing a bug in its PEG parser grammar engine that incorrectly rejected valid tokens from models with large vocabularies. The issue stemmed from a recursive depth limit tied to token character count, which caused failures for tokens exceeding 256 characters, affecting models like GLM-4.7 and Laguna-S-2.1. The fix replaces recursion with an iterative stack-based method, eliminating the depth limit and improving grammar sampling performance. This update ensures reliable structural output constraints for modern LLMs.
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How we got here
- 1Llama.cpp b9870 Release Fixes Long Reasoning Loops
llama.cpp Releases · July 4, 2026 · Same story
- 2llama.cpp fixes JSON schema enforcement in Ling 3.0
llama.cpp Releases · October 4, 2026 · Same story
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