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How We Made a Text-to-Speech Model Respond in Sub-50 ms (nari-labs.com)
toebee 2 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

kamranjon 28 minutes ago [-]
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?
narrationbox 5 minutes ago [-]
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?
bityard 58 minutes ago [-]
How fast is it on consumer-level hardware?
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