time-to-first-audio (TTFA) is critical for realtime voice applications. open source implementations (e.g. vLLM-Omni, SGLang-Omni) are often too slow for production and can have issues with realtime playback if you push for lower latency. we wanted to fix that.
we optimized qwen3-tts, a popular OSS TTS model, to achieve 34 ms p95 TTFA at 10 requests per second on 1 x H100. we open source the implementation and benchmark, as well as a breakdown of how it was done.
Hi there! I actually thought your Dia models were amazing and very natural sounding, I haven’t tried qwen 3 tts yet - has your focus shifted away from building your Dia models and shifted more towards hosting and infrastructure?
its backchanneling frequently makes me laugh to the point of forgetting what i wanted to say. i do like it, it just takes some getting used to, especially since i've been keeping things nice and simple and taking it one step at a time for so long.
time-to-first-audio (TTFA) is critical for realtime voice applications. open source implementations (e.g. vLLM-Omni, SGLang-Omni) are often too slow for production and can have issues with realtime playback if you push for lower latency. we wanted to fix that.
we optimized qwen3-tts, a popular OSS TTS model, to achieve 34 ms p95 TTFA at 10 requests per second on 1 x H100. we open source the implementation and benchmark, as well as a breakdown of how it was done.
github: https://github.com/nari-labs/nari-qwen3-tts
Hi there! I actually thought your Dia models were amazing and very natural sounding, I haven’t tried qwen 3 tts yet - has your focus shifted away from building your Dia models and shifted more towards hosting and infrastructure?
How fast is it on consumer-level hardware?
Haven't read the full report yet, just a quick question. Are your numbers for cold start without pre fill or is it after warmed cache?
chatgpt responds super fast but says filler words like 'hmm..' 'let me think' and responds later with delay
But even then, it's targeting like 300ms not 30ms, right?
its backchanneling frequently makes me laugh to the point of forgetting what i wanted to say. i do like it, it just takes some getting used to, especially since i've been keeping things nice and simple and taking it one step at a time for so long.