Ideogram 3.0 Training
Custom image model training for reusable branded styles, characters, and visual systems
Ideogram 3.0 Training
Custom image model training for reusable branded styles, characters, and visual systems
Ideogram 3.0 Training Overview
Ideogram 3.0 Training is a training workflow for building reusable image models from a curated dataset. It fine-tunes an Ideogram 3.0 model on custom images and optional captions, then produces a trained custom model that can be used in later image generation requests through a custom model URI. It is well suited to brand-consistent imagery, product visuals, recurring characters, packaging systems, and other workflows where teams need a dedicated visual model instead of re-describing the same style in every prompt.
How to Use Ideogram 3.0 Training
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.
More models from Ideogram
Ideogram 4.0 is Ideogram's most capable text-to-image model for design-heavy image generation. It is built for frontier text rendering across languages, structured prompt control through natural language or JSON, bounding-box layout control, transparent background generation, and high-fidelity 2K output. It is well suited to posters, branded graphics, packaging, product visuals, typography-led compositions, and other workflows where design precision matters as much as visual quality.
Ideogram Layerize Text analyzes an image, detects readable text regions, and turns each line into structured editable text blocks with position, styling, and font information. It also returns a text-erased base image, making it useful for posters, social graphics, packaging, book covers, and other design workflows where copy needs to change without regenerating the whole composition.
Ideogram 3.0 Edit lets you inpaint images with surgical control. Upload an image, mask a region, then refine layout or text while the rest stays intact. Ideal for typography fixes, layout tweaks, brand updates, and production safe visual polish in existing assets.
Ideogram 3.0 Remix lets you rework existing images into new styles while it preserves layout and composition. Use it to test creative variants, adjust palettes, or adapt designs for new campaigns. Ideal for A/B testing, rapid iteration, and brand safe visual updates.
Ideogram 3.0 Replace Background removes and swaps image backgrounds while preserving key foreground subjects. Ideal for product mockups, marketing assets, and design overlays where consistent scenes and fast iteration matter for teams and creators.
Ideogram 3.0 Reframe performs style consistent outpainting that extends images beyond their borders. It adapts visuals to new aspect ratios without breaking composition or look. Ideal for repurposing creative, social posts, and design assets for varied formats.
Ideogram 3.0 is a text to image model for high fidelity design work. It improves text rendering, complex layout handling, and photorealism. It also adds stronger style controls and supports editing tasks like inpainting and background replacement for production workflows.
Ideogram 2a Remix lets you reinterpret existing images with controlled style shifts. Feed a base reference image. Generate themed variations, visual transformations, and stylized edits while preserving core layout and content. Ideal for brand updates or creative iterations.
Ideogram 2a is a fast text to image model built for layouts that need clear structure and legible text. It improves prompt following, spatial control, and subject placement. Use it for graphic design workflows, product shots, logos, posters, and quick visual iterations through the API.
Ideogram 2.0 Remix lets you rework existing images while preserving structure and layout. Change styles or mood, adjust composition, and iterate quickly from a reference image. Ideal for designers who need fast visual variants and style exploration from prior outputs.
Ideogram 2.0 Reframe expands existing images with clean outpainting that respects layout and typography. Grow posters or complex compositions to new aspect ratios while preserving style. Ideal for marketing assets, print ready layouts, and large format graphics.
Ideogram 2.0 Edit enables localized inpainting on generated or uploaded images. Select a region, adjust the prompt, and refine logos or text without altering the rest of the frame. Ideal for brand assets, layout tweaks, and fast correction workflows in production apps.
Ideogram 2.0 is a frontier text to image model with strong typography control, improved rendering quality, and better layout consistency. It suits branding workflows, posters, and production design where legible stylized text and precise graphic composition matter to developers.
Ideogram 1.0 Remix lets you transform existing images with new styles and moods. Provide a reference image with a prompt to iterate on layout or typography. Ideal for brand teams that need fast visual variations from a single base concept.
Ideogram 1.0 is a text to image model that focuses on crisp typography and structured layouts. It generates clean illustrations, bold lettering, and stylized compositions with strong visual clarity. Ideal for logos, posters, and graphic design workflows.