Strength Slider Control
A 0–100 numeric scale determines how much the AI transforms the source image — higher values preserve the original more closely, lower values allow greater creative deviation.
Ideogram
Ideogram V3 Remix
Ideogram V3 Remix is an image editing model developed by Ideogram, a company founded by former Google Brain researchers. It extends the base Ideogram V3 image generation model with a remixing system that allows users to transform existing images using text prompts, with a 0–100 strength slider that controls how much the output deviates from the source image. Users can supply their own images or work with images previously generated in Ideogram, and the model will automatically generate a descriptive prompt when an external image is uploaded. The model accepts up to three style reference images to guide color palette, texture, and mood, and supports reusable Style Codes for maintaining brand consistency across outputs. Ideogram is particularly noted for its ability to render legible, correctly spelled text within generated images, making it well-suited for posters, packaging, logos, and marketing materials. It is designed for designers, marketers, and creative professionals who need to iterate on visual concepts without rebuilding them from scratch.
No training date is specified in the available metadata for this model.
10K context
N/A output
Strength Slider Control
Image Input & Upload
Text Prompt Editing
In-Image Text Rendering
Style Reference Inputs
Reproducible Outputs via Seed
Model Overview
High-signal model metadata in a structured two-column overview table.
Provider
The entity that provides this model.
Ideogram
Input Context Window
The number of tokens supported by the input context window.
10K
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
N/A
tokens
Open Source
Whether the model's code is available for public use.
No
Release Date
When the model was first released.
No training date is specified in the available metadata for this model.
Knowledge Cut-off Date
When the model's knowledge was last updated.
No training date is specified in the available metadata for this model.
API Providers
The providers that offer this model. This is not an exhaustive list.
Ideogram
Modalities
Types of data this model can process.
Image
Text
Code
What is Ideogram V3 Remix
A fuller summary of positioning, capabilities, and source-specific details for Ideogram V3 Remix.
Ideogram V3 Remix is an image editing model developed by Ideogram, a company founded by former Google Brain researchers. It extends the base Ideogram V3 image generation model with a remixing system that allows users to transform existing images using text prompts, with a 0–100 strength slider that controls how much the output deviates from the source image. Users can supply their own images or work with images previously generated in Ideogram, and the model will automatically generate a descriptive prompt when an external image is uploaded.
The model accepts up to three style reference images to guide color palette, texture, and mood, and supports reusable Style Codes for maintaining brand consistency across outputs. Ideogram is particularly noted for its ability to render legible, correctly spelled text within generated images, making it well-suited for posters, packaging, logos, and marketing materials. It is designed for designers, marketers, and creative professionals who need to iterate on visual concepts without rebuilding them from scratch.
Capabilities
What Ideogram V3 Remix supports
Image Input & Upload
Accepts an existing image via URL as the remix source; when an external image is uploaded, the model automatically generates a descriptive text prompt to initialize the editing session.
Text Prompt Editing
Accepts a natural language text prompt to guide how the source image is transformed, supporting up to 10,000 characters of prompt input.
In-Image Text Rendering
Generates readable, correctly spelled text embedded within images, making it suitable for posters, logos, packaging, and marketing materials.
Style Reference Inputs
Accepts up to three reference images to guide the color palette, textures, and overall visual mood of the remix, with support for reusable Style Codes.
Reproducible Outputs via Seed
Accepts a seed value as input so that identical prompts and settings produce consistent, reproducible image outputs across runs.
Configurable Generation Options
Exposes multiple select-type parameters — such as aspect ratio, style type, and rendering quality — giving users structured control over output format and appearance.
Pricing for Ideogram V3 Remix
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Input tokens
N/A
Per million tokens
Output tokens
N/A
Per million tokens
API Access & Providers
Places where this model is available, based on the synced detail-page metadata.
Ideogram
Configuration & Parameters
The configurable options currently documented for this model.
Weight
NumberRendering Speed
SelectMagic Prompt
SelectStyle Preset
SelectAspect Ratio
SelectNegative Prompt
TextDescription of what to exclude from an image.
Seed
SeedA specific value that is used to guide the 'randomness' of the generation.
Supported Request Parameters
Parameters currently listed by OpenRouter or the local catalog for this model.
Resources & Documentation
Official model cards, release notes, docs, and other references synced from the source page.
Community discussion
What people think about Ideogram V3 Remix
Ideogram V3 Remix discussions are most active in r/SideProject. The strongest match in this snapshot has 4 upvotes and 2 comments.
**What it does:** Upload a selfie. In 30 seconds, get your color season (Deep Autumn, Soft Summer etc. — 12 total), a 12-color palette, and six AI-generated portraits of you wearing your 4 best and 2 worst colors.
**Live:** https://whatcolorssuitme.com (free, no sign-up required)
**Why I built it:** My partner paid $200 for an in-person color analysis appointment, and the single thing that made the session worth it wasn't the palette — it was seeing the analyst drape different fabrics against her face. The "oh THAT'S the difference" moment. Everything before that was a lecture. I wanted to replicate the drape moment for people who aren't going to drop $200 on a consultation.
**Stack:**
- **Frontend:** Astro on Cloudflare Workers (static SEO pages + SSR for upload flow)
- **Vision:** Claude Sonnet 4.6 with a 3-photo reconciliation prompt — it looks at all 3 photos and explicitly returns the season that is consistent across lighting conditions
- **Portrait generation:** OpenAI gpt-image-1 for the 6 color variants (fires 6 parallel edits), Ideogram V3 remix as fallback if any single variant fails
- **Storage:** Bunny CDN for user selfies + variant outputs, Supabase for analysis records + purchases
- **Payments:** Stripe Checkout (one-time $9 premium for a 24-color PDF handbook)
**Honest numbers after 24h live:**
- 49 SEO pages indexed (12 seasons, 13 Kibbe types, 12 aesthetics, 7 face shapes, 5 body shapes + guides)
- Analysis costs: ~$0.02 Claude Vision + ~$0.12 gpt-image-1 per run — paid tier at $9 has healthy margin
- End-to-end latency: 28s average for 3-photo upload + 6 variant generation
**Things that broke / were tricky:**
- Astro v6 removed `locals.runtime.env` — had to use `import { env } from "cloudflare:workers"` in every API route. Doc wasn't clear on this.
- CSRF protection blocks cross-origin POSTs to `/api/*` by default. Tripped me on the mobile upload flow.
- Stripe `charges_enabled` was false for a week because the onboarding form was missing an ID upload — Stripe doesn't surface this anywhere obvious, had to dig into account capabilities.
- 6-variant generation in parallel = 6 OpenAI tokens of rate-limit headroom gone at once. Had to add retry + fallback per variant, not per request.
**What's next:**
- Face shape + aesthetic detection from same upload (data model already supports it)
- Affiliate fashion links on the premium handbook
- Expo mobile app (already built, waiting on App Store review)
Roast welcome. Happy to answer anything about the stack, economics, or where I got stuck.
FAQ
Common questions about Ideogram V3 Remix
What is the context window for Ideogram V3 Remix?
The model supports a context window of 10,000 characters, which applies to the text prompt input used to guide the image remix.
Does Ideogram V3 Remix have a training data cutoff date?
No training date is specified in the available metadata for this model.
What types of inputs does Ideogram V3 Remix accept?
The model accepts an image URL as the source, a text prompt, a numeric strength value (0–100), a seed for reproducibility, and multiple select-type parameters for options such as aspect ratio, style type, and quality.
Can I use my own photos with Ideogram V3 Remix, or only images generated in Ideogram?
You can use both. The model accepts externally uploaded images via URL in addition to images previously created within Ideogram. When an external image is provided, the model automatically generates a starting prompt based on the image content.
How do style references work in Ideogram V3 Remix?
You can upload up to three reference images to influence the color palette, textures, and mood of the remixed output. Style Codes can be saved and reused to maintain visual consistency across multiple generations.
More models from Ideogram
Continue browsing adjacent models from the same provider.