Ideogram 4.0
open-weight 9.3B text-to-image model
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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 :)
HN · launched Jun 3, 2026 · 46 upvotes (top 17%) · 0 views
Niche: ai image generators · 216 launches, 22 in the last 7 days ▼ -15% · Explore this niche →
Category and tags
- Horizontal
- Content generation
- Developer
- AI-native
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 216 launches in ai image generators →
Could you build this?
No Training a state-of-the-art 9.3B parameter diffusion transformer from scratch demands millions of dollars in compute, huge proprietary image-text datasets, and world-class generative AI research expertise.
What it would actually take: Building this requires a massive training cluster (hundreds of H100 GPUs), billions of curated and filtered image-text pairs with bounding-box annotations, and deep diffusion transformer architectural research. Training pipelines require PyTorch/JAX with distributed techniques (Megatron-LM, FSDP, DeepSpeed) and custom CUDA kernels for attention and spatial guidance. This requires specialized deep learning research teams and substantial capital investment.
Discussion
12 comments analyzed.
Competitors mentioned: Black Forest Labs, Canva (template + text rendering), Draw Things (Apple silicon app), Fal.ai (API router), Stable Diffusion
Concerns raised: Non-commercial license restrictions, Overly aggressive safety filter triggering on natural language prompts, Heavily overcooked images from high default CFG settings, Requires significant manual effort and JSON prompt optimization, Safety filter incorrectly triggered by natural language prompts
Feature requests: Apple silicon / Mac support clarification (GUI vs command line), Integrated template + text rendering with font/position automation, Free LLM for complete end-to-end templating workflow, Improved natural language prompt handling without manual JSON structuring
Competitors
Other products that read as similar to this one : 650 launches clear the similarity bar, closest 8 shown.
Attention rank: #115 of 651 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 215 days after the earliest competitor.
- Ideogram 4.0 · ph · 2026-06-05 · 265 upvotes · similarity 0.66
- A decent text-to-image model trained for ~$20K (Apache 2.0 Weights) · hn · 2026-11-04 · 284 upvotes · similarity 0.52
- RTI · github · 2026-09-10 · 14 upvotes · similarity 0.50
- pjit-21k · github · 2026-11-03 · 55 upvotes · similarity 0.49
- moss-image-forge-neo · github · 2026-10-16 · 15 upvotes · similarity 0.49
- MOSS-Image · github · 2026-10-16 · 1140 upvotes · similarity 0.48
- UltraText_Bench · github · 2026-10-08 · 42 upvotes · similarity 0.45
- 3D AI Art · ph · 2026-10-14 · 1 upvotes · similarity 0.45
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