Image Remixing
Transforms an uploaded source image into a new variation using a text prompt, preserving the original composition and core visual elements while applying creative changes.
Ideogram V2 Remix is an image-to-image generation model developed by Ideogram. Rather than generating images from scratch, it takes an uploaded source image and a text prompt, then produces a transformed version that blends the written creative direction with the original composition and visual elements. It accepts a range of common image formats including jpg, jpeg, png, webp, gif, and avif. The model is designed for designers, artists, and content creators who want to iterate on existing visuals rather than start from a blank canvas. It supports stylistic and thematic transformations guided by natural language, making it useful for exploring concept variations, adapting imagery to new aesthetics, or generating multiple creative directions from a single reference image. A seed input is available for reproducibility, and multiple selection parameters allow control over style, aspect ratio, and other output characteristics.
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A fuller summary of positioning, capabilities, and source-specific details for Ideogram V2 Remix.
Ideogram V2 Remix is an image-to-image generation model developed by Ideogram. Rather than generating images from scratch, it takes an uploaded source image and a text prompt, then produces a transformed version that blends the written creative direction with the original composition and visual elements. It accepts a range of common image formats including jpg, jpeg, png, webp, gif, and avif.
The model is designed for designers, artists, and content creators who want to iterate on existing visuals rather than start from a blank canvas. It supports stylistic and thematic transformations guided by natural language, making it useful for exploring concept variations, adapting imagery to new aesthetics, or generating multiple creative directions from a single reference image. A seed input is available for reproducibility, and multiple selection parameters allow control over style, aspect ratio, and other output characteristics.
Transforms an uploaded source image into a new variation using a text prompt, preserving the original composition and core visual elements while applying creative changes.
Accepts natural language prompts up to 10,000 tokens to direct stylistic and thematic transformations of the source image.
Provides multiple select inputs to control output style, aspect ratio, and other visual parameters for fine-tuned creative direction.
Accepts a numeric seed value to produce reproducible outputs, allowing consistent results across multiple generation runs.
Accepts source images in jpg, jpeg, png, webp, gif, and avif formats via URL input.
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Description of what to exclude from an image.
A specific value that is used to guide the 'randomness' of the generation.
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The model supports a context window of 10,000 tokens, which applies to the text prompt input used to guide image transformation.
The model accepts source images in jpg, jpeg, png, webp, gif, and avif formats, provided via an image URL input.
No. It is an image-to-image model that requires an existing source image as input. It transforms that image based on a text prompt rather than generating a new image from text alone.
Yes. The model accepts a seed value as an input parameter, which allows you to reproduce the same output when using the same source image, prompt, and settings.
The API is available through fal.ai. API reference documentation can be found at https://fal.ai/models/fal-ai/ideogram/v2/remix/api.
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