There have been a lot of strides in open-weight models, well beyond SDXL. Flux, back in August of 2024 was a game changer, finally allowing us to move past SDXL’s nuclear pile of comma-delimited keywords for prompting and allowing more natural language.

And this summer we got Ideogram V4 and Krea2, both of which are highly capable. You can see how the open/closed models have advanced since SDXL in the Progress tab.

https://genai-showdown.specr.net

MJ is pretty out-of-date by this point though it can still be fun from an image space exploration perspective. It scored a rather pitiful 2 out of 15 on my bench back in the summer of 2025.

Progress peaked in 2022?

Otherwise you’re implying the quality plateaued 4 years ago which is ludicrous.

I think with software engineering the biggest jumps have been agentic platforms or work flows. You can create a ticket and this triggers na agent to read the relevant docs and submit an MR, another to validate multiple concerns (correctness, security, performance, costs), another to uodate docs, etc. That's far more impressive than "dev sits down and asks LLM to write code".

With images, I don't see such potential. A builder and a reviewer iterating on improvements? Maybe the reviewer noticing it just needs programmable improvements, eg contrast, color balance etc and triggering a script on top of the LLM generation?

> Feels like ai image generation has plateaud. > Coding related have had massive step-up improvements over time. > The same cannot be said for image generation. If anything, I swear it's gone backwards.

I would argue both are exactly the same. The images are getting nicer, the AI can alter pictures better. It's the same as coding.

The difference is our perception. Looking at image takes 2s, and we can spot what we don't like. Looking at a code change takes hours to understand. It's very difficult to tell how much code generation is improving because almost nobody is reading it.

Image and code generation don't correlate exactly, but I would be surprised to see a big jump of capabilities in either without the other quickly following.

> Feels like ai image generation has plateaud.

I'd bet the future is in combined AI-driven 3D modelling + rendering + AI post-processing. This pipeline solves quite a bit of typical image generation problems.

Your feeling is generally right. There have been no seminal moments in image generation anymore in the last couple of months. Most attention from the big labs has gone to video since that‘s where the money is. We have a page to track the history of it all here https://lumenfall.ai/arena/history

(Right now missing some models which I‘ll add today.)

You could argue that progress has been relatively flat since Nano Banana Pro, but that's still less than a full year old (just barely), and that was the first model that could really fully maintain visual consistency across complex edits. The GPT ones are a little stylistically disappointing in ways, but they've still been making steady progress too. I don't think we can claim a peak just yet, even if it's been slower.

Krea has kept improving editing

There’s less money to be made with images, than code gen.

Investment in new models follows the money.

Seedream 4 continues to be the best model by far at character consistency. I havnt done my tests on this model yet, however.

"It takes 90% of the time to do 90% of the work. The other 10% takes the other 90% of the time"

Turns out you can't brute force art, to the surprise of no one except tech bros.

Coding flattened out like 9 months ago. In reality, people are getting dumber and lazier from over using them, so they feel like they're improving when they aren't really, outside some areas like RE.

In reality RE has only gotten better because they RLd it into the models because the NEED data, so now every kid is decomping proprietary softwate and sending them back great training data.