OpenAI · Photo

GPT Image 1.5 Text-to-Image

Images from textRealistic imagesArtProduct shots

GPT Image 1.5 (T2I) is OpenAI’s fast, cost-efficient text-to-image generator powered by GPT-5 guidance. Create photorealistic shots, product renders, concept art, and stylized graphics from natural-language prompts (optionally conditioned with an image).

from€0.08per render

Use in Genlaxy →

Examples

GPT Image 1.5 Text-to-Image: Street food market in Tokyo at night, chef tossing flaming wok with vegetables mid-air, steam rising, colorful — Prompt
Street food market in Tokyo at night, chef tossing flaming wok with vegetables mid-air, steam rising, colorful paper lanterns overhead, motion blur on crowd in background, vibrant neon signs, photojournalism style
Try this prompt →

GPT Image 1.5 Text-to-Image: Portrait of a cyberpunk hacker, neon pink and blue rim lighting, chrome cybernetic implants on temple, rain dr — Prompt
Portrait of a cyberpunk hacker, neon pink and blue rim lighting, chrome cybernetic implants on temple, rain droplets on skin, dark alley background with holographic advertisements, hyper-detailed, 8K
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GPT Image 1.5 Text-to-Image: Macro photograph of morning dew drops on spider web, each droplet reflecting a tiny forest landscape, soft bok — Prompt
Macro photograph of morning dew drops on spider web, each droplet reflecting a tiny forest landscape, soft bokeh background, golden backlight, extreme detail, nature photography
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GPT Image 1.5 Text-to-Image: Surrealist artwork of a giant whale swimming through clouds above a tiny village, bioluminescent patterns on w — Prompt
Surrealist artwork of a giant whale swimming through clouds above a tiny village, bioluminescent patterns on whale skin, villagers looking up in wonder, dreamlike atmosphere, style of Salvador Dalí meets Hayao Miyazaki
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Specs

Typetext-to-image

OutputPhoto

InputText

Model IDopenai/gpt-image-1.5/text-to-image

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Prices are per render and charged from your balance only when a render succeeds. Failed renders are refunded automatically. Examples show what the model can do; your result depends on your prompt and settings.