Comment by toebee

7 hours ago

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?

  • Hey thank you for your kind words! Yes, we’ve shifted to inference but will also continue doing finetuning etc. on top of open models. Don’t have plans to do pretraining though.

How fast is it on consumer-level hardware?

  • We got a rtx 4090 handling around 10 concurrent requests at 50 ms TTFA after some config changes / adjustment as it doesn’t have FP8. So this 50 ms TTFA thing is very much possible on consumer 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?

  • We do graph capture etc at startup (same as vLLM) but this model variant doesn’t require prefix caching - the prefix is just 10 tokens.