[HN Gopher] Z-Image: Powerful and highly efficient image generat...
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Z-Image: Powerful and highly efficient image generation model with
6B parameters
Author : doener
Score : 203 points
Date : 2025-11-30 11:36 UTC (6 days ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| Copenjin wrote:
| Very good, not always perfect with text or with following exactly
| the prompt, but 6B so... impressive.
| pawelduda wrote:
| Did anyone test it on 5090? I saw some 30xx reports and it seemed
| very fast
| Wowfunhappy wrote:
| Even on my 4080 it's extremely fast, it takes ~15 seconds per
| image.
| egeres wrote:
| Incredibly fast, on my 5090 with CUDA 13 (& the latest
| diffusers, xformers, transformers, etc...), 9 samplig steps and
| the "Tongyi-MAI/Z-Image-Turbo" model I get:
|
| - 1.5s to generate an image at 512x512
|
| - 3.5s to generate an image at 1024x1024
|
| - 26.s to generate an image at 2048x2048
|
| It uses almost all the 32Gb Gb of VRAM and GPU usage. I'm using
| the script from the HF post: https://huggingface.co/Tongyi-
| MAI/Z-Image-Turbo
| danielbln wrote:
| We've come a long way with these image models, and the things you
| can do with paltry 6B are super impressive. The community has
| adopted this model wholesale, and left Flux(2) by the way side.
| It helps that Z-Image isn't censored, whereas BFL (makers of Flux
| 2) dedicated like a fith of their press release talking about how
| "safe" (read: censored and lobotomized) their model is.
| rfoo wrote:
| But this is a CCP model, would it refuse to generate Xi?
| vunderba wrote:
| You tell me.
|
| https://imgur.com/a/7FR3uT1
| CamperBob2 wrote:
| It will generate anything. Xi/Pooh porn, Taylor Swift getting
| squashed by a tank at Tiananmen Square, whatever, no
| censorship at all.
|
| With simplistic prompts, you quickly conclude that the small
| model size is the only limitation. Once you realize how good
| it is with detailed prompts, though, you find that you can
| get a lot more diversity out of it than you initially thought
| you could.
|
| Absolute game-changer of a model IMO. It is competitive with
| Nano Banana Pro in some respects, and that's saying
| something.
| AuryGlenz wrote:
| To be fair, a lot of that was about their online service and
| not the model itself. It can definitely generate breasts.
|
| That said I do find the focus on "safety" tiring.
| xnx wrote:
| Z-Image seems to be the first successor to Stable Diffusion 1.5
| that delivers better quality, capability, and extensibility
| across the board in an open model that can feasibly run locally.
| Excitement is high and an ecosystem is forming fast.
| vunderba wrote:
| I've done some preliminary testing with Z-Image Turbo in the past
| week.
|
| Thoughts
|
| - It's fast (~3 seconds on my RTX 4090)
|
| - Surprisingly capable of maintaining image integrity even at
| high resolutions (1536x1024, sometimes 2048x2048)
|
| - The adherence is impressive for a 6B parameter model
|
| Some tests (2 / 4 passed):
|
| https://imgpb.com/exMoQ
|
| Personally I find it works better as a refiner model downstream
| of Qwen-Image 20b which has significantly better prompt
| understanding but has an unnatural "smoothness" to its generated
| images.
| echelon wrote:
| So does this finally replace SDXL?
|
| Is Flux 1/2/Kontext left in the dust by the Z Image and Qwen
| combo?
| tripplyons wrote:
| SDXL has been outclassed for a while, especially since Flux
| came out.
| aeon_ai wrote:
| Subjective. Most in creative industries regularly still use
| SDXL.
|
| Once Z-image base comes out and some real tuning can be
| done, I think it has a chance of replacing it for the
| function SDXL has
| Scrapemist wrote:
| Source?
| echelon wrote:
| Most of the people I know doing local AI prefer SDXL to
| Flux. Lots of people are still using SDXL, even today.
|
| Flux has largely been met with a collective yawn.
|
| The only thing Flux had going for it was photorealism and
| prompt adherence. But the skin and jaws of the humans it
| generated looked weird, it was difficult to fine tune,
| and the licensing was weird. Furthermore, Flux never had
| good aesthetics. It always felt plain.
|
| Nobody doing anime or cartoons used Flux. SDXL continues
| to shine here. People doing photoreal kept using
| Midjourney.
| vunderba wrote:
| Yeah, I've definitely switched largely away from Flux. Much
| as I do like Flux (for prompt adherency), BFL's baffling
| licensing structure along with its excessive censorship makes
| it a noop.
|
| For ref, the Porcupine-cone creature that ZiT couldn't handle
| by itself in my aforementioned test was easily handled using
| a Qwen20b + ZiT refiner workflow and even with two separate
| models _STILL_ runs faster than Flux2 [dev].
|
| https://imgur.com/a/5qYP0Vc
| amrrs wrote:
| On fal, it takes less than a second many times.
|
| https://fal.ai/models/fal-ai/z-image/turbo/api
|
| Couple that with the LoRA, in about 3 seconds you can generate
| completely personalized images.
|
| The speed alone is a big factor but if you put the model side
| by side with seedream and nanobanana and other models it's
| definitely in the top 5 and that's killer combo imho.
| venusenvy47 wrote:
| I don't know anything about paying for these services, and as
| a beginner, I worry about running up a huge bill. Do they let
| you set a limit on how much you pay? I see their pricing
| examples, but I've never tried one of these.
|
| https://fal.ai/pricing
| tarruda wrote:
| > It's fast (~3 seconds on my RTX 4090)
|
| It is amazing how far behind Apple Silicon is when it comes to
| use non- language models.
|
| Using the reference code from Z-image on my M1 ultra, it takes
| 8 seconds per step. Over a minute for the default of 9 steps.
| nialv7 wrote:
| China really is keeping the open weight/source AI scene alive.
| If in five years a consumer GPU market still exists it would be
| because of them.
| zkmon wrote:
| Just want to learn - who actually needs or buys up generated
| images?
| nine_k wrote:
| Some ideas for your consideration:
|
| - Illustrating blog posts, articles, etc.
|
| - A creativity tool for kids (and adults; consider memes).
|
| - Generating ads. (Consider artisan production and specialized
| venues.)
|
| - Generating assets for games and similar, such as backdrops
| and textures.
|
| Like any tool, it takes certain skill to use, and the ability
| to understand the results.
| zkmon wrote:
| Except for gaming, that doesn't sound like a huge market
| worthy of pouring millions into training these high-quality
| models. And there is a lot of competition too. I suspect
| there are some other deep-pocketed customers for these
| images. Probably animations? movies? TV ads?
| pixl97 wrote:
| Propaganda?
| leobg wrote:
| Dying businesses like newspapers and local banks, who use it to
| save the money they used to spend on shutterstock images?
| That's where I've seen it at least. Replacing one useless
| filler with another.
| wongarsu wrote:
| I follow an author who publishes online on places like
| Scribblehub and has a modestly successful Patreon. Over the
| years he has spent probably tens of thousands of dollars on
| commissioned art for his stories, and he's still spending
| heavily on that. But as image models have gotten better this
| has increasingly been supplemented with AI-images for things
| that are worth a couple dollars to get right with AI, but not a
| couple hundred to get a human artist to do them
|
| Roughly speaking the art seems to have three main functions:
|
| 1. promote the story to outsiders: this only works with human-
| made art
|
| 2. enhance the story for existing readers: AI helps here, but
| is contentious
|
| 3. motivate and inspire the author: works great with AI. The
| ease of exploration and pseudo-random permutations in the
| results are very useful properties here that you don't get from
| regular art
|
| By now the author even has an agreement with an artist he
| frequently commissions that he can use his style in AI art in
| return for a small "royalty" payment for every such image that
| gets published in one of his stories. A solution driven both by
| the author's conscience and by the demands of the readers
| Youden wrote:
| During the holiday season I've been noticing AI-generated
| assets on tons of meatspace ads and cheap, themed products.
| nine_k wrote:
| It's amazing how much knowledge about the world fits into 16 GiB
| of the distilled model.
| echelon wrote:
| This is early days, too. We're probably going to get better at
| this across more domains.
|
| Local AI will eventually be booming. It'll be more
| configurable, adaptable, hackable. "Free". And private.
|
| Crude APIs can only get you so far.
|
| I'm in favor of intelligent models like Nano Banana over
| ComfyUI messes (the future is the model, not the node graph).
|
| I still think we need the ability to inject control layers and
| have full access to the model, because we lose too much utility
| by not having it.
|
| I think we'll eventually get Nano Banana Pro smarts slimmed
| down and running on a local machine.
| bobsmooth wrote:
| >Local AI will eventually be booming.
|
| With how expensive RAM currently is, I doubt it.
| bogwog wrote:
| Yeah I know right?? Just a few more trillion dollars bro and
| it'll be good bro
| echelon wrote:
| Is this a joke?
|
| Image and video models are some of the most useful tools of
| the last few decades.
| muglug wrote:
| The [demo PDF](https://github.com/Tongyi-
| MAI/Z-Image/blob/main/assets/Z-Ima...) has ~50 photos of
| attractive young women sitting/standing alone, and exactly two
| photos featuring young attractive men on their own.
|
| It's incredibly clear who the devs assume the target market is.
| bobsmooth wrote:
| The ratio of naked female loras compared to naked male loras,
| or even non-porn loras, on civitai is at least 20 to 1. This
| shouldn't be surprising.
| abbycurtis33 wrote:
| They're correct. This tech, like much before it, is being
| driven by the base desires of extremely smart young men.
| IncreasePosts wrote:
| Not just extremely smart young men, but probably young men
| who fall closer to the incel category than normal go-on-
| tinder-and-find-a-date category.
| pixl97 wrote:
| I mean spending all that time on dates, and wives, and kids
| gives you much less time to build AI models.
|
| The people with the time and desire to do something are the
| ones most likely to do it, this is no brilliant
| observation.
| IncreasePosts wrote:
| You could say that about any field, and yet we don't see
| the same behavior in most other fields
|
| Spending all your time on dates and wives and kids means
| you're not spending all your time building houses.
| abbycurtis33 wrote:
| With today's remote social validation for women and all
| time low value of men due to lower death rates and the
| disconnect from where food and shelter come from, lonely
| men make up a huge portion of the population.
| Manuel_D wrote:
| Something like >80% of men consume sexually explicit media.
| It's hardly limited to involuntarily celibate men.
| IncreasePosts wrote:
| It's not about consumption, it's about having a vast
| majority of your demo being sexy women instead of a
| balance.
| cma wrote:
| They maybe have an rhlf phase, but I mean there is also just
| the shape of the distribution of images on the internet and,
| since this is from alibaba, their part of the internet/social
| media (Weibo) to consider
| iamflimflam1 wrote:
| The model is uncensored, so will probably suite that target
| market admirably.
| thih9 wrote:
| Please write what you mean instead of making veiled
| implications. What is the point of beating around the bush
| here?
|
| It's not clear to me what you mean either, especially since
| female models are overwhelmingly more popular in general[1].
|
| [1]: "Female models make up about 70% of the modeling industry
| workforce worldwide" https://zipdo.co/modeling-industry-
| statistics/
| muglug wrote:
| > Female models make up about 70% of the modeling industry
| workforce worldwide
|
| Ok so a ~2:1 ratio. Those examples have a 25:1 ratio.
| killingtime74 wrote:
| It's interesting the handsome guy is literally Tony Leung Chiu-
| wai, https://www.imdb.com/name/nm0504897/, not even modified
| AuryGlenz wrote:
| Considering how gaga r/stablediffusion is about it, they
| weren't wrong. Apparently Flux 2 is dead in the water even
| though the knowledge it has contained in the model is way, way
| higher than Z-Image (unsurprisingly).
| BoorishBears wrote:
| Flux 2[dev] is awful.
|
| Z-Image is getting traction because it fits on their tiny
| GPUs and does porn sure, but even with more compute Flux
| 2[dev] has no place.
|
| Weak world knowledge, worse licensing, and it ruins the #1
| benefit of a larger LLM backbone with post-training for JSON
| prompts.
|
| LLMs already understand JSON, so additional training for JSON
| feels like a cheaper way to juice prompt adherence than more
| robust post-training.
|
| And honestly even "full fat" Flux 2 has no great spot: Nano
| Banana Pro is better if you need strong editing, Seedream 4.5
| is better if you need strong generation.
| cess11 wrote:
| "The Internet is really, really great..."
|
| https://www.youtube.com/watch?v=LTJvdGcb7Fs
| mhb wrote:
| Maybe both women and men prefer looking at attractive women.
| khimaros wrote:
| i have been testing this on my Framework Desktop. ComfyUI
| generally causes an amdgpu kernel fault after about 40 steps
| (across multiple prompts), so i spent a few hours building a
| workaround here
| https://github.com/comfyanonymous/ComfyUI/pull/11143
|
| overall it's fun and impressive. decent results using LoRA. you
| can achieve good looking results with as few as 8 inference
| steps, which takes 15-20 seconds on a Strix Halo. i also created
| a llama.cpp inherence custom node for prompt enhancement which
| has been helping with overall output quality.
| xfalcox wrote:
| We have vLLM for running text LLMs in production. What is the
| equivalent for this model?
| mh- wrote:
| I would say there's isn't an equivalent. Some people will
| probably tell you ComfyUI - you can expose workflows via API
| endpoints and parameterize them. This is how e.g. Krita AI
| Diffusion uses a ComfyUI backend.
|
| For various reasons, I doubt there are any large scale SaaS-
| style providers operating this in production today.
| idontwantthis wrote:
| Does it run on apple silicon?
| iamflimflam1 wrote:
| It's working for me - it does max out my 64GB though.
| sheepscreek wrote:
| Wow. I always forget how unlike autoregressive models,
| diffusion models are heavier on resources (for the same
| number of parameters).
| sheepscreek wrote:
| Apparently - https://github.com/ivanfioravanti/z-image-mps
|
| Supports MPS (Metal Performance Shaders). Using something that
| skips Python entirely along with a mlx or gguf converted model
| file (if one exists) will likely be even faster.
| BoredPositron wrote:
| I wish they would have used the WAN vae.
| thih9 wrote:
| As an AI outsider with a recent 24GB macbook, can I follow the
| quick start[1] steps from the repo and expect decent results? How
| much time would it take to generate a single medium quality
| image?
|
| [1]: https://github.com/Tongyi-MAI/Z-Image?tab=readme-ov-
| file#-qu...
| altmanaltman wrote:
| If you don't know anything about AI in terms of how these
| models are run, comfyui's macos version is probably the easiset
| to use. There is already a Z-Image workflow that you can get
| and comfyui will get all the models you need and get it work
| together. Can expect decent speed
| thih9 wrote:
| I'm fine with the quick start steps and I prefer CLI to GUI
| anyway. But if I try it and find it too complex, I now know
| what to try instead - thanks.
|
| I'm still curious whether this would run on a MacBook and how
| long would it take to generate an image. What machine are you
| using?
| egeozcan wrote:
| Have a 48GB M4 Pro and every inference step takes like 10
| seconds on a 1024x1024 image. so six steps and you need a
| minute. Not terrible, not great.
| aleyan wrote:
| I have a 24GB M5 macbook pro. In ComfyUI using default z-image
| workflow, generating a single image just took me 399 seconds,
| during which the computer froze and my airpods lost audio.
|
| On replicate.com a single image takes 1.5s at a price of 1000
| images per $1. Would be interesting to see how quick it is on
| ComfyUI Cloud.
|
| Overall, running generative models locally on Macs seems very
| poor time investment.
| cubefox wrote:
| I'm particularly impressed by the fact that they seem to aim for
| photorealism rather than the semi-realistic AI-look that is
| common in many text-to-image models.
| CamperBob2 wrote:
| Exactly, and at the same time, if you _want_ an affected style,
| all you have to do is ask for it.
| bilsbie wrote:
| What kind of rig is required to run this?
| CamperBob2 wrote:
| The simple Python example program runs great on almost any GPU
| with 8 GB or more memory. Takes about 1.5 seconds per iteration
| on a 4090.
|
| The bang:buck ratio of Z-Image Turbo is just bonkers.
| reactordev wrote:
| My issue with this model is it keeps producing Chinese people and
| Chinese text. I have to very specifically go out of my way to say
| what kind of race they are.
|
| If I say "A man", it's fine. A black man, no problem. It's when I
| add context and instructions is just seems to want to go with
| some Chinese man. Which is fine, but I would like to see more
| variety of people it's trained on to create more diverse images.
| For non-people it's amazingly good.
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