toebee
Joined 4 years ago
Karma
427
Submissions
68
Member since
Jan 12
Recent submissions
Comment · 1 month ago
if we can lower the pricing by not 50% but 10x, then I think it would be something people want. we are taking the bet that OSS models will take a huge chunk of market share not just in LLMs but in multimodal as well
Comment · 1 month ago
thank you Dylan!
Comment · 1 month ago
agreed. we've been doing some work around NVIDIA personaplex 7b, but its quality is quite far from GPT-Live-1, esp in terms of intelligence. Once a good OSS model is out, we'll be sure to be the first to serve it cheaply to the masses :)
Comment · 1 month ago
awesome! will look into Darwin TTS. super interesting
Comment · 1 month ago
the qwen3-asr inference repo is not OSSed as of now. we're planning to write a paper or tech report on it as it contains some general techniques for ASR inference.
Comment · 1 month ago
hey, thanks for letting us know! will look into the issue and see what went wrong.
Comment · 1 month ago
very cool. will try for local use!
Comment · 1 month ago
thanks for the interest! we have a blog post on exactly how we did it: https://narilabs.com/blog/qwen3-tts-speed-cost-frontier/
Comment · 1 month ago
thanks for the feedback! will investigate and get it fixed
Comment · 1 month ago
hey sorry about that, you can here a few of our voices here: https://narilabs.com/product/qwen3-tts/
Comment · 1 month ago
Qwen3-ASR 1.7B is an excellent OSS Speech-to-Text model. But it is slow out of the box. We built an inference engine around it, and now it is the fastest realtime transcription model (as of Sep 2026) at 40 ms time-to-final-segment (TTFS). And the word error rate (WER) sits top 3 on Coval’s independent benchmarks. OSS will win, not just in LLMs but also in multimodal, one step at a time.
Comment · 1 month ago
Hey HN, Toby from Nari Labs here.
Our TTS endpoints for Qwen3-TTS 1.7B are live:
> "Fast" endpoint: client-side p90 time-to-first-audio (TTFA) at 50ms.
> "Standard" endpoint: dirt cheap at $5 per 1M characters, still faster than industry avg at 200 ms TTFA.
TTFA is measured using our OSS benchmarking tool from us-west-1 and us-east-1 (https://github.com/nari-labs/benchmarks.git).
Quality: link to TTS samples (https://narilabs.com/blog/introducing-nari-qwen3-tts/). Based on preliminary benchmarks by a 3rd-party (Speko AI), we scored above leading TTS providers such as Grok and Rime (https://narilabs.com/blog/qwen3-tts-speko-benchmark/)!
We are working hard on further lowering the price of our endpoints, as well as adding more voices and support for input streaming.
We believe open-source will win - not just in LLMs but also in multimodal :) During public beta, all endpoints are free. Try it out and let me know how it goes!