Overview

Ideogram 3.0 Training is a training workflow for creating a reusable custom image model from your own dataset.

It is built for teams that want a model aligned to a specific visual identity, product line, character set, illustration style, or brand system. Instead of steering a general model with repeated prompt instructions, the training step produces a dedicated custom model that can later be used directly in image generation requests.

What It Does

Trains Custom Models From Proprietary Datasets

The workflow lets you create a dataset, upload training images, and start a training run that fine-tunes an Ideogram 3.0 model on that material. This makes it useful for organizations that want a model shaped by their own assets rather than generic public styles.

Supports Image and Caption Based Supervision

Training data can include images together with optional captions. Captions help the model learn stronger prompt-to-style alignment and make the resulting model more controllable during later generation.

Produces a Reusable Generation Model

The output of the training workflow is a custom model, not a one-off image batch. Once training is complete, the resulting model can be referenced in downstream generation requests through a custom_model_uri.

Helps Maintain Style Consistency

This is useful for workflows where visual consistency matters across campaigns, product imagery, branded graphics, recurring characters, or packaging systems. A custom trained model reduces the amount of prompt repetition needed to stay on style.

Fits Structured Dataset Workflows

Ideogram's custom model flow includes dataset creation, asset upload, model training, and model listing. This makes it a good fit for teams that want a more structured training pipeline rather than ad hoc style prompting.

Best Fit

• Brand-consistent image generation
• Product and packaging visual systems
• Recurring character or mascot workflows
• Proprietary illustration or design styles
• Teams building reusable internal image models

Input and Output

• AIR ID: ideogram:3.0@training
• Input: a curated training dataset of images, with optional captions
• Output: a trained custom Ideogram model that can be used in later image generation requests
• Dataset guidance: supports image datasets with optional caption files; high-quality and visually coherent datasets produce better results

Notes

• This workflow is about model creation, not one-off image generation.
• The resulting model is intended to carry the style or subject patterns of the dataset into future generations.
• Dataset quality, consistency, and captioning have a large impact on the usefulness of the trained model.
• The currently documented provider flow uses Ideogram 3.0 generation endpoints together with a trained custom model reference.