OpenAI · Foto

GPT Image 1.5 Text-to-Image

Bilder aus TextRealistische BilderKunstProduktfotos

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).

ab0,08 €pro Rendering
In Genlaxy verwenden →

Beispiele

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

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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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Technische Daten

Typtext-to-image
AusgabeFoto
EingabeText
Modell-IDopenai/gpt-image-1.5/text-to-image

Ähnliche Modelle

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Die Preise gelten pro Rendering und werden nur bei erfolgreichem Rendering von Ihrem Guthaben abgebucht. Fehlgeschlagene Renderings werden automatisch erstattet. Die Beispiele zeigen, was das Modell kann; Ihr Ergebnis hängt von Ihrem Prompt und Ihren Einstellungen ab.