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Gemma 4 12B audio attention issues with long prompts

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๐Ÿฆ™Read original on Reddit r/LocalLLaMA

๐Ÿ’กTroubleshooting a critical attention bottleneck in Gemma 4 12B for unified audio-text voice applications.

โšก 30-Second TL;DR

What Changed

Gemma 4 12B fails to process audio when system prompts exceed ~21k tokens.

Why It Matters

This limitation restricts the use of unified models for complex voice-assistant tasks requiring extensive system instructions. Developers may need to adopt multi-model architectures until the attention mechanism is optimized.

What To Do Next

If building a voice assistant, implement a two-stage pipeline using a smaller model for audio transcription before passing text to the 12B model.

Who should care:Developers & AI Engineers

Key Points

  • โ€ขGemma 4 12B fails to process audio when system prompts exceed ~21k tokens.
  • โ€ขThe issue persists across multiple stacks including vLLM, llama.cpp, and LiteRT-LM.
  • โ€ขSmaller prompts allow the model to correctly attend to audio, suggesting an attention saturation bottleneck.
  • โ€ขUsers are currently using smaller models as audio front-ends to bypass the limitation.
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Original source: Reddit r/LocalLLaMA โ†—