Open Source · Cerebras · Google · Hugging Face
The demo is published as a real-time speech-to-speech pipeline
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★ Tier-1 Source
This creates a fully open speech-to-speech loop: The architecture brings together the strength of the open-source AI ecosystem: Cerebras for fast inference, Google DeepMind’s Gemma 4 31B for the language model, and Qwen for text-to-speech.
Key facts
- This same Hugging Face speech-to-speech pipeline already powers Reachy Mini robots, with more than 9,000 robots in the wild
- The architecture brings together the strength of the open-source AI ecosystem: Cerebras for fast inference, Google DeepMind’s Gemma 4 31B for the language model, and Qwen for text-to-speech
- For robots, voice assistants, and embodied AI, responsiveness is not a cosmetic improvement
- This collaboration reflects a shared belief that the future of AI will be both open and performant
Summary
Today, some production systems see a reasonable median latency while still experiencing frustrating multi-second delays at the P95. Cerebras helps solve one of the most important bottlenecks in the stack: the language-model response time. This same Hugging Face speech-to-speech pipeline already powers Reachy Mini robots, with more than 9,000 robots in the wild. This collaboration reflects a shared belief that the future of AI will be both open and performant.