Individual skill
ideogram-ultra
Build Ideogram 4 (Ideogram Ultra) txt2img and img2img workflows with the local open-weights model, dual conditional/unconditional models with DualModelGuider, Qwen3-VL text encoder, and structured JSON ("compositional deconstruction") prompts for strong text rendering and layout control
plugin/skills/ideogram-ultra/SKILL.md
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- agent-skills Repository topic
- ai-agent Repository topic
- claude-code Repository topic
- claude-plugin Repository topic
- comfyui Repository topic
- comfyui-extension Repository topic
- flux Repository topic
- image-generation Repository topic
- mcp Repository topic
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# Ideogram 4 (Ideogram Ultra) Workflows
## Overview
**This is a LOCAL open-weights pipeline, NOT the hosted Ideogram API.** There is no API key, no `IdeogramGenerate` API node, and no network call at generation time. Comfy-Org released the Ideogram 4 weights on Hugging Face and they run entirely on your GPU via standard `UNETLoader` / `CLIPLoader` / `VAELoader` nodes. (Note: ComfyUI *also* ships separate API/"partner" nodes that call the paid hosted Ideogram service. That is a different thing and is not what this workflow uses.)
Ideogram 4 is best known for **text rendering / typography**, **poster and graphic-design layouts**, and **prompt adherence**. The hallmark of this workflow is a **structured JSON prompt** (a "compositional deconstruction" caption with bounding boxes) instead of a plain text prompt. This is what gives precise control over where text and objects land in the frame.
Source workflow this skill is derived from: `IDEOGRAM_ULTRA_WORKFLOW-V2.json` (UI format, 66 nodes, 4 subgraphs), by Aitrepreneur. It provides both a **TEXT TO IMAGE** path and an **IMAGE TO IMAGE** path.
### Two unusual things to know up front
1. **Dual models.** Two UNETs are loaded: a conditional model (`ideogram4_fp8_scaled`) and an `..._unconditional_fp8_scaled` model. A `DualModelGuider` node uses both to perform asymmetric classifier-free guidance; the unconditional model provides the CFG baseline. There is **no negative text prompt**; negative conditioning is `ConditioningZeroOut`.
2. **Two text models, different jobs.**