Ideogram launches Ideogram 4.0 as its first open-weight text-to-image model, enabling JSON prompting and bounding box controls

@ideogram_ai Using bounding boxes is a top 1 experience

2. A full style LoRA, four days after the weights dropped. Trained on 100 images, basic AI Toolkit settings.

The style is consistent in every element: new characters, new scenes, even lettering.

Images by u/TheDudeWithThePlan on r/StableDiffusion

5. Dual character LoRA with spot on identity and zero bleed.

With 4.0's regional captioning and prompting capabilities, each identity stays locked to its own region of the frame.

"This is the first model I have been able to make this work on."

One week ago, we released Ideogram 4.0, our first open weight model.

Since the launch, the open-source and creative communities have pushed it beyond what we could imagine. Seems like JSON and bounding box prompting is becoming the new norm now.

Week one community highlights (thread):

9. CRT screens with detailed scan-lines, screen curvature, and reflections.

"There's just something about the fidelity and details that no other model can do."

Images by u/Beautiful_Egg6188 on r/StableDiffusion

1. JSON bounding box prompting increases customization and accuracy at the same time.

Every element gets its own caption and position for where it belongs, and 4.0 renders what you placed, where you placed it.

Images by u/Far_Insurance4191 on r/StableDiffusion

3. Each image below is Seed 1. First generation, no cherry picking, no re-rolls.

No upscaling or post processing. Generated at 2 megapixels on an RTX 3060ti with 8GB of VRAM.

Images by u/Puzzled-Valuable-985 on r/StableDiffusion

4. Control is becoming the most popular topic around 4.0.

You can now get the same results that require 100 seeds on other local models in just a few generations. High quality text rendering on the first try lets users to focus on the rest of the image.

Images by u/Objective_Junket_713 on r/StableDiffusion

6. Users built prompt compilers to turn natural language and images into JSON prompts.

This one runs qwen 3.6 27B locally. Top comment: "the knowledge this model has is unmatched for local and for only 9.3b."

Images by u/Producing_It on r/StableDiffusion

7. Generations with cinema-grade composition.

Dozens of repeated figures and mirrored reflections, with zero collapse. Commenters called it another level of coherence and control.

Images by u/Beautiful_Egg6188 on r/StableDiffusion

8. Comic book pages and storyboards, generated panel by panel with bounding boxes.

Exact panels, speech bubbles, and lettering, total control over the page. Every panel stays consistent, even without a LoRA.

Images by u/echothought on r/StableDiffusion

Within a week, the community built trainers, prompt compilers, LoRAs, and entire workflows.

Reply with your best generations and we'll include them in our next community highlights thread.

@ideogram_ai I didn't realise I was so hooked on boxes because of a generative AI model

@ideogram_ai yeah im using it locally, it's so good

@ideogram_ai Open creativity unleashed, community soaring

@ideogram_ai Very interesting.

Open source makes AI move faster.

@ideogram_ai Very cool, Always bet on open source 🔥🔥

@ideogram_ai You really released something great here. Thank you.

@ideogram_ai I am on my phone right now so can't really upload the images I created. But, really hatsoff to you guys and thank you for such an awesome model. It's a marvel. I pushed it real hard real far on a 5070.

@mo_norouzi this is what happens when tooling becomes part of the creative language prompting itself starts evolving into a design system n great product entices great community that extend n improves the product