Two undergrads. One still in the military. Zero funding.
One ridiculous goal: build a TTS model that rivals NotebookLM Podcast, ElevenLabs Studio, and Sesame CSM.
Somehow… we pulled it off. Here’s how 👇
Nemotron VoiceChat from @nvidia listens and responds in audio while also calling external tools to retrieve information or perform tasks.
We build an inference engine that handles 64 sessions on a single H100 GPU while handling tool-calls effectively.
blog: narilabs.com/blog/making-too…
vLLM-omni does 1 session per GPU. NVIDIA's own NIM and C++ inference engines are each capable of 4 and 6 concurrent sessions on 1x H100.
At 64 sessions, the cost to run S2S sits at around 6.7 cents per hour, per user.
Stop guessing which speech model is fastest or cheapest.
Pick up to 3, set your language, and see latency, price per minute, and capabilities next to each other.
Speech to text, text to speech, and language models.
Try it: platform.speko.ai
Our TTS and STT endpoints are now live at @speko_ai: Openrouter for voice AI
We're sitting at #1 in latency in both STT and TTS on Speko benchmarks. And our STT endpoint is top 2 in terms of accuracy beating out Deepgram, Meta, and Gemini.
Try it out: speko.ai
heavily requested feature: input streaming for Qwen3-TTS is now GA!
stream your LLM outputs into our TTS endpoint so you can output audio before the LLM is finished ✅
Just added word timestamps support to our Qwen3-ASR streaming endpoint - using the 0.6B forced aligner model. Still the same latency and cost!
Blog: narilabs.com/blog/word-level…
Duplex speech is the frontier of Speech AI and PersonaPlex 7B from @nvidia is the most adopted OSS duplex model.
We achieve 80 concurrent sessions on a single H100 GPU, costing below 10 cents an hour per user to serve. GPT-Live costs 10 cents per 2 minutes.
Read more: narilabs.com/blog/personaple…
There's still a long way to go before OSS models reach the intelligence and naturalness of models such as GPT-Live. But we are bullish about the future of open duplex models and will continue to build infra to serve them to the masses, cheaply.
Diarization is a key problem in speech. And Pyannote is the king of diarization. Used it for all of Dia's data pipelines.
Through various optimizations, we got Pyannote's flagship OSS model to process 100+ hours of audio in under 100 seconds. on a single A100 GPU.
Read more: narilabs.com/blog/making-pya…
Did I mention prices?
> STT: #2 cheapest
> TTS: tied for #1 cheapest
Try now at narilabs.com for FREE.
Benchmark values are based on Sep 14 15:00 UTC, only comparing publicly available endpoints.
Today we’re launching:
> the world's fastest Speech-to-Text endpoint at 40 ms time-to-final-segment (TTFS)
> the world's cheapest streaming Speech-to-Text endpoint at $0.06 / hr
Powered by Qwen3-ASR 1.7B on Nari Labs inference engine.
🔠 Top 3 Accuracy on Coval Benchmarks
🚀 3x faster than ElevenLabs Scribe V2
💸 9x cheaper than Gemini Transcribe 3.5
✅ available FREE for a limited time
We believe open-source will win - not just in LLMs, but also in multimodal AI. Nari Labs is here to accelerate that future, starting with speech.
Try now at narilabs.com
We are a small team of ex-YC, ex-KRAFTON research engineers. We built Dia, the first OSS model for natural dialogue w/ 2M+ downloads and ~20k Github Stars. Our team has published on ICLR / NeurIPS and earned 3 IOI and ICPC gold medals. @trynarilabs is backed by @ycombinator
We’re just getting started. More to come in Speech, Audio, Video, and World Models.
Stay tuned. narilabs.com