Gemma 4 31B fails at file-editing tasks due to text formatting mismatches
A developer reported that the Gemma 4 31B model, served in bf16 precision via vLLM, consistently fails file-editing tasks across multiple coding harnesses. The model gets stuck in loops because it generates minor mismatches, such as incorrect indentation, when trying to recall and replace original code blocks. This issue highlights a common failure mode in LLM-based coding agents where strict search-and-replace mechanisms reject edits due to minor formatting discrepancies. It underscores the need for more robust edit tools that can tolerate minor syntax or indentation variations during code modification. The user experienced these failures across several coding harnesses, including Goose, Copilot, and Little Coder, despite using an updated chat template that improved benchmark scores. The proposed workaround includes developing edit tools that ignore indentation or whitespace differences when matching code blocks.
## BACKGROUND
AI coding assistants often edit files by identifying a specific block of existing code and replacing it with new code. vLLM is a high-throughput serving engine used to run large language models locally, while bf16 (bfloat16) is a 16-bit floating-point format that optimizes memory usage during inference. Goose is an open-source AI developer agent designed to automate coding tasks by interacting with local directories and APIs.