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LatestStability AI4.0
Stability AIText → Image

Ideogram 4.0 arrives as an open-weight image model

A 9.3-billion-parameter text-to-image system lands with open weights and a public GitHub home.

Jun 3, 2026
NotableOther

The Ideogram OSS team has released Ideogram 4.0, an open-weight text-to-image model with roughly 9.3 billion parameters. The release was announced through a Show HN post pointing to the project's GitHub repository, where the weights and supporting code are published.

At 9.3B parameters, Ideogram 4.0 sits in a practical middle ground for image generation: large enough to aim for strong prompt fidelity, but small enough to run on a single high-end GPU rather than demanding a cluster. The model is distributed under a custom license, so teams considering commercial use will want to read the terms before building on top of it.

Why it matters

Open-weight image models remain comparatively scarce next to the flood of open language models, and each credible release widens the options for developers who want to fine-tune, self-host, or audit a generator rather than calling a closed API.

  • Open weights: the model can be downloaded and run locally.
  • 9.3B parameters: a size geared toward accessible inference.
  • Custom license: usage rights are not a standard permissive license, so check the details.

As always with a fresh release, independent evaluation will be the real test. The repository is the place to watch for documentation, sample outputs, and community benchmarks as people put Ideogram 4.0 through its paces.

Sources

  • Show HN: Ideogram 4.0 – open-weight 9.3B text-to-image model

    Hacker News

    Visit
OlderMiniMax Releases M3, a Multimodal MoE ModelMiniMax · Vision-Language · 5 months agoNewerBoson AI's Higgs Audio v3 Offers Expressive, Multilingual TTSBosonai · Text → Speech · 5 months ago

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Specs

Parameters9.3B
LicenseOTHER
Downloads72.1K
Likes860

Can you run it?

Runs on a laptop — about 10.3 GB at FP8.

  • BF16 (as published)

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    19.6 GB
  • FP8

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    10.3 GB
Your machine
  • Precision not published; assuming 16-bit (BF16) weights.
  • Parameter count is an editorial estimate — no weights metadata on Hugging Face.
  • Covers the published checkpoint; text encoders and VAE loaded alongside may add a few GB (many runtimes offload them to CPU).

Estimated from the parameter count. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text → Image
3 versions — view changelog

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