HuggingFace
7/10 signal
Hugging Face and Cerebras bring Gemma 4 to real-time voice AI
tool-use
What happened
Hugging Face and Cerebras have demonstrated an open, modular, real-time speech-to-speech pipeline designed to minimize latency. The cascaded stack uses Nvidia's Parakeet for speech-to-text, Google's Gemma 4 31B running on Cerebras' ultra-fast inference hardware, and Alibaba's Qwen3TTS for text-to-speech. This setup aims to solve the multi-second latency bottlenecks (especially at P95) that break natural voice interactions.
Why it matters
Open-source, modular voice stacks are becoming viable alternatives to proprietary real-time voice APIs by optimizing inference hardware.
The take
While native multimodal models (like GPT-4o voice) are the gold standard, this open, cascaded stack proves that developers can build highly responsive, fully customizable voice agents using open-source models. Leveraging Cerebras' hardware for the LLM bottleneck is a smart way to keep latency low enough for natural conversation without relying on closed APIs.
Do this
Check out the Hugging Face/Cerebras GitHub repository to benchmark this open speech-to-speech stack for your own real-time voice agent applications.
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