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[ARTICLE · art-33844] src=discuss.huggingface.co ↗ pub= topic=large-language-models verified=true sentiment=↓ negative

Gemma 4 bug fixes and Research Request

A critical bug in Google's Gemma 4 causes it to malform tool calls under real load, affecting vLLM, llama.cpp, Ollama, and oobabooga. A developer open-sourced a diagnosis, repair, and experimental LoRA that reduces but doesn't eliminate the issue, calling for community help with richer data.

read1 min views1 publishedJun 19, 2026

Gemma-4 has an ecosystem-wide agentic bug: under real load (long context + reasoning + generating

content) it malforms its own tool calls and then loops on the broken output — reported across vLLM,

llama.cpp, Ollama, and oobabooga, and unfixed by Google.

I open-sourced a full diagnosis + a reproduction harness + a working parser-level repair + a stock

NVFP4 quant & recipe + an experimental format LoRA — with all raw data. Honest findings: the LoRA

reduces the slip (I ruled out quantization as the cause via a BF16 control) but doesn’t fully

eliminate it yet — it overfit my synthetic data, so a bigger/more-diverse dataset is likely the real fix.

Everything’s here, Built with Gemma — looking for help pushing the LoRA further with richer data

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