GLM-Image image model

GLM-Image is an open-source image-making model from Z.ai that uses both autoregressive and diffusion decoder parts.

It was released on January the 14th 2025.

Its image quality is similar to common latent diffusion methods, but it's better when it comes to adding text or handling stuff that needs real knowledge. It gets the meaning right and handles complex info well while still making detailed and high-quality images.

Besides turning text into images, it can also change images in other ways like editing, style changes, keeping someone’s look the same, and keeping different parts of an image consistent.

Because the inference optimizations for this architecture are currently limited, the runtime cost is still relatively high. It requires either a single GPU with more than 80GB of memory, or a multi-GPU setup.

Redditors' Early Feedback:

GLM-Image feels more like a tech test than something you'd use every day.

People like the idea behind it, mixing autoregressive methods with diffusion, but they say it still falls short in speed, usability, and how the images look. Distilled diffusion models are faster and usually look better.

What it does well. It’s supposed to handle text and layouts better than others. A few examples looked okay, but there were still typos and weird letters. Fonts remind folks of GPT-Image-style stuff.

It seems to get what prompts are asking for. That gives it potential for stuff like diagrams or info-heavy pics later on.

People often say this model isn't meant to compete right now. More like a stepping stone for what might come next. Some users even liked that the team shared it early, bugs and all.

Main complaints. The image style gets called overdone or fake. Faces and hands usually come out rough. Some say it looks a year behind.

Text quality let folks down. Spelling problems and bent letters were a big letdown, especially for something built to handle text better.

It’s slow. Making one image can take over a minute, even on strong machines. Compared to models that spit out pictures in seconds, it feels too heavy.

Most users just don’t see a reason to pick GLM right now. It’s hard to justify with faster, smaller tools out there.

In head-to-heads...

Z-Image Turbo wins big on speed, look, and realism. Even people who don’t love it admit it outperforms its size.

Flux.2 Dev is better at sticking to prompts and doing edits or inpainting. Its pics sometimes feel stiff or off in anatomy, but it still ranks above GLM for real use.

Qwen 2512 hits a middle ground. It follows prompts better than Z-Image and looks better than GLM. If users had to pick just one, this often gets the nod.

Big picture. There’s a clear divide. One group wants results now. They think GLM is slow and clunky. The other group says this is just a test to show autoregressive image generation can work. Not about winning today.

Everyone agrees on one thing though: GLM isn’t ready for daily use. Right now it’s more of an example of what hybrid models might become later, GLM is something to keep an eye on.