Study finds LLM accuracy drops more from missing punctuation than heavy typos

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A developer ran roughly 4,900 prompt sessions across 12 AI models — including Claude, Gemma, Llama, and Mistral variants — to test how spelling errors and punctuation breaks affect response accuracy. Models like Claude Opus 5 and Fable 5.1 scored 100% even when 70% of words were misspelled, and handled non-native grammar without any accuracy loss. However, a single missing or misplaced punctuation mark with perfect spelling caused the same top models to drop by 8 to 23 percentage points. The most damaging error was a missing closing quotation mark, which caused models to miscount word occurrences by conflating quoted and unquoted text. The findings suggest users should prioritize structural punctuation accuracy over spelling correctness when writing AI prompts.

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