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.
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.
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”.
Yep, this has been the reality now for years. Scammers have already had access to it. I remember an article years ago about a grandma who wired her life savings to a scammer who claimed to have her granddaughter held hostage in a foreign country. Turns out they just cloned her voice from Facebook data and knew her schedule so timed it while she would be unreachable by phone.
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.
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.
There are plenty of electronic artists who can't sing. Right now they have to hire someone else to do the singing for them, but I'd wager a lot of them would like to own their music end-to-end. I would.
I'm a filmmaker. I've done it photons-on-glass production for fifteen years. Meisner trained, have performed every role from cast to crew. I'm elated that these tools are going to enable me to do more with a smaller budget. To have more autonomy and creative control.
Yes, the flipside of this is that we're eroding the last bit of ability for people to make a living through their art. We are capturing the market for people to live off of making illustrations, to making background music, jingles, promotional videos, photographs, graphic design, and funnelling those earnings to NVIDIA. The question I keep asking is whether we care to value as a society for people to make a living through their art. I think there is a reason to care.
It's not so much of an issue with art for art's sake aided by AI. It's an issue with artistic work becoming unviable work.
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.
Interesting model, I've managed to get the 0.6B param model running on my old 1080 and I can generated 200 character chunks safely without going OOM, so I thought that making an audiobook of the Tao Te Ching would be a good test. Unfortunately each snippet varies drastically in quality: sometimes the speaker is clear and coherent, but other times it bursts out laughing or moaning. In a way it feels a bit like magical roulette, never being quite certain of what you're going to get. It does have a bit of charm, when you chain the various snippets together you really don't know what direction it's gonna go.
Using speaker Ryan seems to be the most consistent, I tried speaker Eric and it sounded like someone putting on a fake exaggerated Chinese accent to mock speakers.
If it wasn't for the unpredictable level of emotions from each chunk, I'd say this is easily the highest quality TTS model I've tried.
Have you tried specifying the emotion? There's an option to do so and if it's left empty it wouldn't surprise me if it defaulted to rng instead of bland.
With a good harness I am getting similar results with GLM 4.7. I am paying for TWO! max accounts and my agents are running 24/7.
I still have a small Claude account to do some code reviews. Opus 4.5 does good reviews but at this point GLM 4.7 usually can do the same code reviews.
If cost is an issue (for me it is, I pay out of pocket) go with GLM 4.7
Have you tested alternatives? I grabbed Open Code and a Minimax m2.1 subscription, even just the 10usd/mo one to test with.
Result? We designed a spec for a slight variation of a tool for which I wrote a spec with Claude - same problem (process supervisor tool), from scratch.
Honestly, it worked great, I have played a little further with generating code (this time golang), again, I am happy.
I've been using GLM 4.7 with Claude Code. best of both worlds. Canceled my Anthropic subscription due to the US politics as well. Already started my "withdrawal" in Jan 2025, Anthropic was one of the few that was left
The Chinese labs distill the SOTA models to boost the performance of theirs. They are a trailer hooked up (with a 3-6 month long chain) to the trucks pushing the technology forwards. I've yet to see a trailer overtake it's truck.
China would need an architectural breakthrough to leap American labs given the huge compute disparity.
Care to explain how the volume of AI research papers authored by Chinese researchers[1] has exceeded US-published ones? Time-traveling plagiarism perhaps, since you believe the US is destined to lead always.
1. Chinese researcher in China, to be more specific.
Not a great metric, research in academia doesn't necessarily translate to value. In the US they've poached so many academics because of how much value they directly translate to.
Perhaps you should pay attention to where the puck is going to be, rather than where it is currently. Lots of original ideas are coming out of Chinese AI research[1], denying this betrays some level of cope.
1. e.g. select any DeepSeek release, and read the accompanying paper
Agreed. I do think the metaphor still holds though.
A financial jackknifing of the AI industry seems to be one very plausible outcome as these promises/expectations of the AI companies starts meeting reality.
I think the least politically divisive issue within the US is concern about China’s growth as it directly threatens the US’s ability to set the world’s agenda. It may be politically divisive if you are aligned with Chinese interests but I don’t see anything politically divisive for a US audience. I expect Chinese CEOs speak in similar terms to a Chinese audience in terms of making sure they’re decoupled from the now unstable US political machine.
From the perspective of competing against China in terms of AI the argument against open models makes sense to me. It’s a terrible problem to have really. Ideally we should all be able to work together in the sandbox towards a better tomorrow but thats not reality.
I prefer to have more open models. On the other hand China closes up their open models once they start to show a competitive edge.
I've been using GLM 4.7 alongside Opus 4.5 and I can't believe how bad it is. Seriously.
I spent 20 minutes yesterday trying to get GLM 4.7 to understand that a simple modal on a web page (vanilla JS and HTML!) wasn't displaying when a certain button was clicked. I hooked it up to Chrome MCP in Open Code as well.
It constantly told me that it fixed the problem. In frustration, I opened Claude Code and just typed "Why won't the button with ID 'edit' work???!"
It fixed the problem in one shot. This isn't even a hard problem (and I could have just fixed it myself but I guess sunk cost fallacy).
I've used a bunch of the SOTA models (via my work's Windsurf subscription) for HTML/CSS/JS stuff over the past few months. Mind you, I am not a web developer, these are just internal and personal projects.
My experience is that all of the models seem to do a decent job of writing a whole application from scratch, up to a certain point of complexity. But as soon as you ask them for non-trivial modifications and bugfixes, they _usually_ go deep into rationalized rabbit holes into nowhere.
I burned through a lot of credits to try them all and Gemini tended to work the best for the things I was doing. But as always, YMMV.
Amazingly, just yesterday, I had Opus 4.5 crap itself extensively on a fairly simple problem -- it was trying to override a column with an aggregation function while also using it in a group-by without referring to the original column by its full qualified name prefixed with the table -- and in typical Claude fashion it assembled an entire abstraction layer to try and hide the problem under, before finally giving up, deleting the column, and smugly informing me I didn't need it anyway.
That evening, for kicks, I brought the problem to GLM 4.7 Flash (Flash!) and it one-shot the right solution.
It's not apples to apples, because when it comes down to it LLMs are statistical token extruders, and it's a lot easier to extrude the likely tokens from an isolated query than from a whole workspace that's already been messed up somewhat by said LLM. That, and data is not the plural of anecdote. But still, I'm easily amused, and this amused me. (I haven't otherwise pushed GLM 4.7 much and I don't have a strong opinion about about it.)
But seriously, given the consistent pattern of knitting ever larger carpets to sweep errors under that Claude seems to exhibit over and over instead of identifying and addressing root causes, I'm curious what the codebases of people who use it a lot look like.
I use Opus 4.5 for planning, when I reach my usage limits fallback to GLM 4.7 only for implementing the plan, it still struggles, even though I configure GLM 4.7 as both smaller model and heavier model in claude code
it isn't often that tehcnology gives me chills, but this did it. I've used "AI" TTS tools since 2018 or so, and i thought the stuff from two years ago was about the best we were going to get. I don't know the size of these, i scrolled to the samples. I am going to get the models set up somewhere and test them out.
Now, maybe the results were cherrypicked. i know everyone else who has released one of these cherrypicks which to publish. However, this is the first time i've considered it plausible to use AI TTS to remaster old radioplays and the like, where a section of audio is unintelligible but can be deduced from context, like a tape glitch where someone says "HEY [...]LAR!" and it's an episode of Yours Truly, Johnny Dollar...
I have dozens of hours of audio of like Bob Bailey and people of that era.
scroll down to the second to last group, the second one down is obama speaking english, the third one down is trump speaking japanese (a translation of the english phrase)
besides, they know what side their bread is buttered on. I feel like this is almost not the real announcement; or, the engineers that wrote this up and did the demos just ran it that way. The normal speech voices are fine (lower than the anime ones on the page.) i agree that the first few are very infantile. I'll change that word if i can think of a better one.
Indeed, I have a future project/goal of "restoring" Have Gun - Will Travel radio episodes to listenable quality using tech like this. There are so many lines where sound effects and tape rot and other "bad recording" things make it very difficult to understand what was sad. Will be amazing, but as with all tech the potential for abuse is very real
hey if you want to collab or trade notes, my email is in my profile.
there was java software that did FANTASTIC work cleaning up crappy transfers of audio, like, specifically, it was perfect for "AM Quality Monaural Audio".
Observe, original: https://www.youtube.com/watch?v=YiRcOVDAryM
my edit (took about an hour, if memory serves, to set up. forgot render time...): https://www.youtube.com/watch?v=xazubVJ0jz4
i say "was [...] software" because the last 2 times i've tried to use it, it did imperceptible cleanup, making it worthless. Anyhow, all my radio plays are from OTRR, i think.
Audio.Restoration.DeNoise.DeNoiseLF.2.8.3_WiN.OSX is a more recent version i think
Can anyone please provide directions/links to tools that can be run locally, and that take an audio recording of a voice as an input, and produce an output with the same voice saying the same thing with the same intonations, but with a fixed/changed accent?
This is needed for processing an indie game's voice recordings, where the voice actors weren't native speakers and had some accent.
Haha something that I want to try out. I have started using voice input more and more instead of typing and now I am on my second app and second TTS model, namely Handy and Parakeet V3.
Parakeet is pretty good, but there are times it struggles. Would be interesting to see how Qwen compares once Handy has it in.
Has anyone successfully run this on a Mac? The installation instructions appear to assume an NVIDIA GPU (CUDA, FlashAttention), and I’m not sure whether it works with PyTorch’s Metal/MPS backend.
FWIW you can run the demo without FlashAttention using --no-flash-attn command-line parameter, I do that since I'm on Windows and haven't gotten FlashAttention2 to work.
I see a lot of references to `device_map="cuda:0"` but no cuda in the github repo, is the complete stack flash attention plus this python plus the weights file, or does one need vLLM running as well?
Well, if you look at the prompts, they are basically told to sound like that.
And if you ask me, I think these models were trained on tween fiction podcasts. (My kids listen to a lot of these and dramatic over-acting seems to be the industry standard.)
Also, their middle-aged adult with an "American English" accent sounds like any American I've ever met. More like a bad Sean Connery impersonator.
The real value I see is being able to clone a voice and change timbre and characteristics of the voice to be able to quickly generate voice overs, narrations, voice acting, etc. It's superb!
I shared a recording of audio I generated with that here: https://simonwillison.net/2026/Jan/22/qwen3-tts/
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.
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.
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 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).
That said, I am likewise looking forward to the cool things to come out of this.
I was with you, until
But, yeah. Life will go on.
I'm a filmmaker. I've done it photons-on-glass production for fifteen years. Meisner trained, have performed every role from cast to crew. I'm elated that these tools are going to enable me to do more with a smaller budget. To have more autonomy and creative control.
It's not so much of an issue with art for art's sake aided by AI. It's an issue with artistic work becoming unviable work.
What am I doing wrong?
Using speaker Ryan seems to be the most consistent, I tried speaker Eric and it sounded like someone putting on a fake exaggerated Chinese accent to mock speakers.
If it wasn't for the unpredictable level of emotions from each chunk, I'd say this is easily the highest quality TTS model I've tried.
> Read this in a calm, clear, and wise audiobook tone.
> Do not rush. Allow the meaning to sink in.
But maybe I should experiment with something more detailed. Do you have any suggestions?
Although I like the model, I don't like the leadership of that company and how close it is, how divisive they're in terms of politics.
I still have a small Claude account to do some code reviews. Opus 4.5 does good reviews but at this point GLM 4.7 usually can do the same code reviews.
If cost is an issue (for me it is, I pay out of pocket) go with GLM 4.7
Have you tested alternatives? I grabbed Open Code and a Minimax m2.1 subscription, even just the 10usd/mo one to test with.
Result? We designed a spec for a slight variation of a tool for which I wrote a spec with Claude - same problem (process supervisor tool), from scratch.
Honestly, it worked great, I have played a little further with generating code (this time golang), again, I am happy.
Beyond that, Glm4.7 should also be great.
See https://dev.to/kilocode/open-weight-models-are-getting-serio...
It is a recent case story of vibing a smaller tool with kilo code, comparing output from minimax m2.1 and Glm4.7
Honestly, just give it a whirl - no need to send money to companies/nations your disagree with with.
$20/month is a bit of an insane ask when the most valuable thing Anthropic makes is the free Claude Code CLI.
China would need an architectural breakthrough to leap American labs given the huge compute disparity.
1. Chinese researcher in China, to be more specific.
1. e.g. select any DeepSeek release, and read the accompanying paper
A financial jackknifing of the AI industry seems to be one very plausible outcome as these promises/expectations of the AI companies starts meeting reality.
What do you mean by this?
https://www.bloomberg.com/news/articles/2026-01-20/anthropic...
And that's the rub.
Many of us are not.
I prefer to have more open models. On the other hand China closes up their open models once they start to show a competitive edge.
Being critical of favorable actions towards a rival country shouldn't be divisive, and if it is, well, I don't think the problem is in the criticism.
Also the link doesn't mention open source? From a google search, he doesn't seem to care much for it.
I spent 20 minutes yesterday trying to get GLM 4.7 to understand that a simple modal on a web page (vanilla JS and HTML!) wasn't displaying when a certain button was clicked. I hooked it up to Chrome MCP in Open Code as well.
It constantly told me that it fixed the problem. In frustration, I opened Claude Code and just typed "Why won't the button with ID 'edit' work???!"
It fixed the problem in one shot. This isn't even a hard problem (and I could have just fixed it myself but I guess sunk cost fallacy).
My experience is that all of the models seem to do a decent job of writing a whole application from scratch, up to a certain point of complexity. But as soon as you ask them for non-trivial modifications and bugfixes, they _usually_ go deep into rationalized rabbit holes into nowhere.
I burned through a lot of credits to try them all and Gemini tended to work the best for the things I was doing. But as always, YMMV.
That evening, for kicks, I brought the problem to GLM 4.7 Flash (Flash!) and it one-shot the right solution.
It's not apples to apples, because when it comes down to it LLMs are statistical token extruders, and it's a lot easier to extrude the likely tokens from an isolated query than from a whole workspace that's already been messed up somewhat by said LLM. That, and data is not the plural of anecdote. But still, I'm easily amused, and this amused me. (I haven't otherwise pushed GLM 4.7 much and I don't have a strong opinion about about it.)
But seriously, given the consistent pattern of knitting ever larger carpets to sweep errors under that Claude seems to exhibit over and over instead of identifying and addressing root causes, I'm curious what the codebases of people who use it a lot look like.
I use Opus 4.5 for planning, when I reach my usage limits fallback to GLM 4.7 only for implementing the plan, it still struggles, even though I configure GLM 4.7 as both smaller model and heavier model in claude code
Now, maybe the results were cherrypicked. i know everyone else who has released one of these cherrypicks which to publish. However, this is the first time i've considered it plausible to use AI TTS to remaster old radioplays and the like, where a section of audio is unintelligible but can be deduced from context, like a tape glitch where someone says "HEY [...]LAR!" and it's an episode of Yours Truly, Johnny Dollar...
I have dozens of hours of audio of like Bob Bailey and people of that era.
besides, they know what side their bread is buttered on. I feel like this is almost not the real announcement; or, the engineers that wrote this up and did the demos just ran it that way. The normal speech voices are fine (lower than the anime ones on the page.) i agree that the first few are very infantile. I'll change that word if i can think of a better one.
Audio.Restoration.DeNoise.DeNoiseLF.2.8.3_WiN.OSX is a more recent version i think
p.s. are you a "dude named Ben"?
This is needed for processing an indie game's voice recordings, where the voice actors weren't native speakers and had some accent.
Parakeet is pretty good, but there are times it struggles. Would be interesting to see how Qwen compares once Handy has it in.
There are some samples. If you have GPU you might want to fork and improve this, but otherwise slow, but usable on CPU as well.
And if you ask me, I think these models were trained on tween fiction podcasts. (My kids listen to a lot of these and dramatic over-acting seems to be the industry standard.)
Also, their middle-aged adult with an "American English" accent sounds like any American I've ever met. More like a bad Sean Connery impersonator.
100% I was thinking the same thing.
Edit: "Cross-lingual Voice Clone" https://qwen.ai/blog?id=qwen3tts-0115#voice-clone