How does GPT Image compare to Flux Pro?

GPT Image has superior prompt understanding for complex descriptions, while Flux Pro offers better fine detail and faster generation. Flux Pro is generally better for straightforward requests; GPT Image shines when your prompt is long and complex.

Is GPT Image the same as DALL-E?

GPT Image is OpenAI newest image generation model, separate from the DALL-E series. It is built on more recent architecture and significantly outperforms DALL-E 3 in quality, prompt adherence, and versatility.

Why is GPT Image more expensive than Flux Pro?

GPT Image uses a larger model with more compute-intensive inference. The higher cost reflects the advanced language understanding and complex scene rendering capabilities. For simpler prompts, Flux Pro at 3 credits offers similar visual quality.

Does GPT Image support editing and inpainting?

Yes. GPT Image supports both image-to-image transformation and mask-based inpainting. Its strong language understanding makes it particularly good at following specific editing instructions.

GPT Image 2

GPT Image by OpenAI combines world-class language understanding with image generation. It excels at following complex, nuanced prompts and producing images that precisely match detailed descriptions, including scenes with specific spatial relationships and interactions.

เริ่มสร้าง ดูผลงาน

โมเดล

ข้อมูลจำเพาะ

ข้อมูลจำเพาะของโมเดล

ความละเอียดสูงสุด

ความเร็ว

~12s per image

ราคา / เครดิต

10 credits / image

ความสามารถ

ฟีเจอร์ที่รองรับ

AI Text to Image Generator

AI Image to Image

ทำงานอย่างไร

ฟีเจอร์หลัก

Superior Prompt Understanding

Built on GPT architecture, this model understands complex, multi-paragraph prompts with spatial relationships, conditionals, and nuanced descriptions better than any other image model.

Complex Scene Composition

Describe a scene with multiple subjects, specific positions, actions, and interactions. GPT Image arranges elements logically and maintains spatial consistency.

Reliable Text in Images

Strong text rendering capabilities for signs, labels, headlines, and decorative typography. Combined with its prompt understanding, it handles text placement instructions precisely.

ผลงาน