Ideogram 4.0

In plain words

Ideogram 4.0 is an open-weight text-to-image model that generates design-ready images with bounding-box layout control and multilingual text rendering. It produces native 2K resolution output and is built for developers and enterprises integrating visual AI into applications. The model supports social media and design workflows.

written from the facts on this page · September 2026

From the sources

Ideogram 4.0 is an open-weight text-to-image model trained from scratch, with bounding-box layout control, multilingual text rendering, and native 2K output. For developers and enterprises building on visual AI.

Ideogram 4.0 is an open weight image model: dense text rendering across languages, object and text placement through bounding box control, and 2K output that doesn

Built for design: open weights, multilingual text, precise layout control, editable elements, and realistic 2K images. Chromium outran every closed browser engine, PyTorch is the dominant ML framework, and most of the internet runs on open source software. Over the past year, proprietary image models have set a new standard on text rendering, prompt adherence, and photorealism, while open weight models have fallen behind. Today, we are releasing Ideogram 4.0 as a state-of-the-art open weight image model for developers and enterprises to build with us. The weights are yours to download , fine-tune, and run on your own hardware. Commercial deployments come with a license that matches your…from ideogram.ai

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  Ideogram 4.0 – open-weight 9.3B text-to-image modelJun 2026 · github.com · ▲46

  It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)

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