GPT Image 1.5 Edit is OpenAI’s image model for precise, natural-language edits. Add/remove objects, swap backgrounds, retouch faces, adjust colors/lighting, edit text/graphics, crop/resize, and apply hex color control. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
GPT Image 1.5 Edit is OpenAI’s image model for precise, natural-language edits. Add/remove objects, swap backgrounds, retouch faces, adjust colors/lighting, edit text/graphics, crop/resize, and apply hex color control. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Cada ejecución costará 0.009. Con $10 puedes ejecutar aproximadamente 1111 veces.
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{
"model": "openai/gpt-image-1.5/edit"
}Necesitas iniciar sesión para acceder al historial de solicitudes del modelo.
Iniciar SesiónGPT Image 1.5 Edit is a cost-efficient image editing model powered by OpenAI’s GPT image technology. It enables users to refine, modify, or transform existing images using natural language instructions, while maintaining the original style, composition, and visual integrity.
Understands complex textual instructions and applies targeted edits that match intent and context.
Add, remove, or modify elements in an image with precision — from subtle adjustments to full stylistic transformations.
Accepts one or more image inputs to guide the edit or style reference process.
Preserves the key artistic or photographic features, such as lighting, tone, and pose, while applying changes only where needed.
Professional-quality visual editing at low cost, ideal for rapid prototyping, design iteration, or creative workflows.
| Parameter | Description |
|---|---|
prompt* | Describe how you want to edit or modify the image (e.g. “change outfit colors to pastel tones, add neon city lights in the background”) |
images* | Upload one or more reference images (JPG / PNG) to be edited or used as visual input |
quality | Output quality tier: low, medium, or high |
input_fidelity | Allows you to better preserve details from the input images in the output. This is especially useful when using images that contain elements like faces or logos that require accurate preservation in the generated image. |
size | Output size: 1024×1024, 1024×1536, or 1536×1024 |
Three fashionable young women in a nighttime urban scene, showcasing Y2K and streetwear aesthetics. Each has distinct styling: plaid shirt with ripped jeans, off-shoulder top with retro socks and chunky sneakers, crop top with cowboy boots and accessories. Enhance lighting and color balance for a cinematic look.