Comment by simonw
1 day ago
If you want to try out the voice cloning yourself you can do that an this Hugging Face demo: https://huggingface.co/spaces/Qwen/Qwen3-TTS - switch to the "Voice Clone" tab, paste in some example text and use the microphone option to record yourself reading that text - then paste in other text and have it generate a version of that read using your voice.
I shared a recording of audio I generated with that here: https://simonwillison.net/2026/Jan/22/qwen3-tts/
This is terrifying. With this and z-image-turbo, we've crossed a chasm. And a very deep one. We are currently protected by screens, we can, and should assume everything behind a screen is fake unless rigorously (and systematically, i.e. cryptographically) proven otherwise. We're sleepwalking into this, not enough people know about it.
That was my thought too. You’d have “loved ones” calling with their faces and voices asking for money in some emergency. But you’d also have plausible deniability as anything digital can be brushed off as “that’s not evidence, it could be AI generated”.
Only if you focus on the form instead of the content. For a long time my family has had secret words and phrases we use to identify ourselves to each other over secure, but unauthenticated, channels (i.e. the channel is encrypted, but the source is unknown). The military has had to deal with this for some time, and developed various form of IFF that allies could use to identify themselves. E.g. for returning aircraft, a sequence of wing movements that identified you as friend. I think for a small group (in this case, loved ones), this could be one mitigation of that risk. My parents did this with me as a kid, ostensibly as a defense against some other adult saying "My mom sent me to pick you up...". I never did hear of that happening, though.
this was already possible with chatterbox for a long while.
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For now you could ask them to turn away from the camera while keeping their eyes open. If they are a Z-Image they will instantly snap their head to face you.
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> as anything digital can be brushed off as “that’s not evidence, it could be AI generated”.
This won't change anything about Western style courts which have always required an unbroken chain of custody of evidence for evidence to be admissable in court
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https://www.youtube.com/watch?v=diboERFAjkE pretty much this
That's a reupload of Cybergem's video. https://www.youtube.com/watch?v=-gGLvg0n-uY
Oh wow. Thank you for this. Amazing, terrifying, spot on, all of it.
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> This is terrifying.
Far more terrifying is Big Tech having access to a closed version of the same models, in the hands of powerful people with a history of unethical behavior (i.e. Zuckerberg's "Dumb Fucks" comments). In fact it's a miracle and a bit ironic that the Chinese would be the ones to release a plethora of capable open source models, instead of the scraps like we've seen from Google, Meta, OpenAI, etc.
> Far more terrifying is Big Tech having access to a closed version of the same model
Agreed. The only thing worse than everyone having access to this tech is only governments, mega corps and highly-motivated bad actors having access. They've had it a while and there's no putting the genii back in the bottle. The best thing the rest of us can do is use it widely so everyone can adapt to this being the new normal.
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I do strongly agree. Though the societal impact is only mitigated by open models, not curtailed at all.
>Far more terrifying is Big Tech having access to a closed version of the same models, in the hands of powerful people with a history of unethical behavior (i.e. Zuckerberg's "Dumb Fucks" comments).
Lol what exactly do you think Zuck would do with your voice, drain your bank account??
I'd be a bit more worried with Z-Image Edit/Base is release. Flux.2 Klein is our and its on par with Zit, and with some fine tuning can just about hit Flux.2. Adding on top of that is Qwen Image Edit 2511 for additional refinement. Anything is possible. Those folks at r/StableDiffusion and falling over the possible release of Z-Image-Omni-Base, a hold me over until actual base is out. I've heard its equal to Flux.2. Crazy time.
Admittedly I have not dove into it much but, I wonder if we might finally have a usecase for NFTs and web3? We need some sort of way to denote items are persion generated not AI. Would certainly be easier than trying to determine if something is AI generated
That's the idea behind C2PA[1], your camera and the tools put a signature on the media to prove its provenance. That doesn't make manipulation impossible (e.g. you could photograph an AI image of a screen), but it does give you a trail of where a photo came from and thus an easier way to filter it or lookup the original.
[1] https://c2pa.org/
How would NFTs/web3 help differentiate between something created by a human and something that a human created with AI and then tagged with their signature using those tools?
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> With this and z-image-turbo, we've crossed a chasm.
And most of all: they're both local models. The cat is out of the box and it's never going back in. There's no censoring of this. No company that can pull the plug. Anyone with a semi-modern GPU can use these models.
We're going to be okay.
There are far more good and interesting use cases for this technology. Games will let users clone their voices and create virtual avatars and heroes. People will have access to creative tools that let them make movies and shows with their likeness. People that couldn't sing will make music.
Nothing was more scary than the invention of the nuclear weapon. And we're all still here.
Life will go on. And there will be incredible benefits that come out of this.
I'm not denigrating the tech, all I'm saying is that we've crossed to new territory and there will be consequences that we don't understand from this. The same way that social media has been particularly detrimental to young people (especially women) in a way we were not ready for. This __smells__ like it could be worse, alongside with (or regardless of) the benefits of both.
I simply think people don't really know that the new world requires a new set of rules of engagement for anything that exists behind a screen (for now).
We'll be okay eventually, when society adapts to this and becomes fully aware of the capabilities and the use cases for abuse. But, that may take some time. The parent is right to be concerned about the interim, at the very least.
That said, I am likewise looking forward to the cool things to come out of this.
Yeah. Not using voice, but...https://nymag.com/intelligencer/article/white-house-posts-fa...
> We're going to be okay.
> And there will be incredible benefits that come out of this.
Your username is echelon.
I just wanted to point that out.
> Nothing was more scary than the invention of the nuclear weapon. And we're all still here.
Except that building a nuclear weapon was not available to everyone, certainly not to dumb people whose brain have been feeded with social media content.
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> People that couldn't sing will make music.
I was with you, until
But, yeah. Life will go on.
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The HF demo space was overloaded, but I got the demo working locally easily enough. The voice cloning of the 1.7B model captures the tone of the speaker very well, but I found it failed at reproducing the variation in intonation, so it sounds like a monotonous reading of a boring text.
I presume this is due to using the base model, and not the one tuned for more expressiveness.
edit: Or more likely, the demo not exposing the expressiveness controls.
The 1.7B model was much better at ignoring slight background noise in the reference audio compared to the 0.6B model though. The 0.6B would inject some of that into the generated audio, whereas the 1.7B model would not.
Also, without FlashAttention it was dog slow on my 5090, running at 0.3X realtime with just 30% GPU usage. Though I guess that's to be expected. No significant difference in generation speed between the two models.
Overall though, I'm quite impressed. I haven't checked out all the recent TTS models, but a fair number, and this one is certainly one of the better ones in terms of voice cloning quality I've heard.
How did you do this locally? Tools? Language?
I just followed the Quickstart[1] in the GitHub repo, refreshingly straight forward. Using the pip package worked fine, as did installing the editable version using the git repository. Just install the CUDA version of PyTorch[2] first.
The HF demo is very similar to the GitHub demo, so easy to try out.
That's for CUDA 12.8, change PyTorch install accordingly.
Skipped FlashAttention since I'm on Windows and I haven't gotten FlashAttention 2 to work there yet (I found some precompiled FA3 files[3] but Qwen3-TTS isn't FA3 compatible yet).
[1]: https://github.com/QwenLM/Qwen3-TTS?tab=readme-ov-file#quick...
[2]: https://pytorch.org/get-started/locally/
[3]: https://windreamer.github.io/flash-attention3-wheels/
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Any idea on the VRAM footprint for the 1.7B model? I guess it fits on consumer cards but I am wondering if it works on edge devices.
The demo uses 6GB dedicated VRAM on Windows, but keep in mind that it's without FlashAttention. I expect it would drop a bit if I got that working.
Haven't looked into the demo to see if it could be optimized by moving certain bits to CPU for example.
Remarkable tech that is now accessible to almost anyone. My cloned voice sounded exactly like me. The uses for this will be from good to bad and everywhere in-between. A deceased grandmother reading "Good Night Moon" to grandkids, scamming people, the ability to create podcasts with your own voices from just prompts.
It's a good thing governments (https://www.ato.gov.au/online-services/voice-authentication) and banks (https://www.anz.com.au/security/how-we-protect-you/voice-id/) haven't gone all in on using voice as an authentication mechanism.
I got some errors trying to run this on my MBP. Claude was able to one-shot a fix.
``` Loaded speech tokenizer from ~/.cache/huggingface/hub/models--Qwen--Qwen3-TTS-12Hz-1.7B-VoiceDesign/snapshots/0e711a1c0aa5aad30654426 e0d11f67716c1211e/speech_tokenizer Fetching 11 files: 0%| | 0/11 [00:00<?, ?it/s]Fetching 11 files: 100%|| 11/11 [00:00<00:00, 125033.45it/s] The tokenizer you are loading from '!/.cache/huggingface/hub/models--Qwen--Qwen3-TTS-12Hz-1.7B-VoiceDesign/snapshots/0e711a1c0aa5aad30654426e0d11f67716c1211e' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instr.... This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. ```
I cloned my voice and had it generate audio for a paragraph from something I wrote. It definitely kind of sounds like me, but I like it much better than listening to my real voice. Some kind of uncanny peak.
They weirdly makes it a canny peak though :)
You do realize that you don't hear your real voice normally, an individual has to record their voice to hear how others hear their voice. What you hear when you speak includes your skull resonating, which other's do not hear.
> The requested GPU duration (180s) is larger than the maximum allowed
What am I doing wrong?
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Hello, the recording you posted does not tell much about the cloning capability without an example from your real voice.
Given how easy voice cloning is with this thing I chickened out of sharing the training audio I recorded!
That's not really rational considering the internet is full of examples of my voice that anyone could use though. Here's a recent podcast clip: https://www.youtube.com/watch?v=lVDhQMiAbR8&t=3006s
Thanks, so it’s in the [pretty close but still distinguishable] range.
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It was fun to try out. I wonder if at some point if I have a few minutes of me talking I could make myself read an entire book to myself.