openai/gpt-image-2

OpenAI's state-of-the-art image generation model. Create and edit images from text with strong instruction following, sharp text rendering, and detailed editing.

$0.1 / request
GPU: H100

Pricing

openai/

gpt-image-2

Pricing for Synexa AI models works differently from other providers. Instead of being billed by time, you are billed by input and output, making pricing more predictable.

Output
$0.1000 / image
or
10 images / $1

For example, generating 100 images should cost around $10.00.

Check out our docs for more information about how per-request pricing works on Synexa.

ProviderPrice ($)Saving (%)
Synexa$0.1000-
replicate$0.128021.9%

Readme

GPT Image 2 is OpenAI's state-of-the-art image generation model. Create images from text or edit existing images with precise, instruction-following control.

What it does

GPT Image 2 handles two workflows: generating images from text descriptions, and editing existing images with specific instructions. It's designed to follow your directions closely while keeping the parts you want unchanged. When you pass reference images, GPT Image 2 processes them at high fidelity automatically — pass one image to edit it, or pass multiple images (up to 20) to combine styles, subjects, or references into a single output.

Key capabilities

  • Photorealism and detail: Natural-looking images with accurate lighting, believable materials, and rich textures.
  • Text rendering: Dense text, small lettering, and complex layouts like infographics, UI mockups, and marketing materials.
  • Precise editing: Targeted changes without reinterpreting the entire image. Preserves identity, composition, and lighting while you adjust specific elements.
  • Style control: Apply consistent visual styles across different subjects, or transfer the look of one image to another with minimal prompting.
  • World knowledge: Built-in reasoning lets the model understand contextual references in prompts.

Use cases

  • Image generation: Infographics, logos, UI mockups, photorealistic scenes, comic strips, marketing visuals.
  • Image editing: Style transfer, virtual clothing try-ons, product mockups, text translation in images, lighting adjustments, object removal, scene compositing.
  • Character consistency: Multi-page illustrations where characters look the same across different scenes.

How to get good results

  • Be specific: Describe what you want clearly. "Add soft coastal daylight" beats "make it better."
  • Use photo language for realism: Mention lens type, lighting quality, and framing for photorealistic results.
  • Lock what shouldn't change: When editing, explicitly state what must stay the same.
  • Put text in quotes: For readable text in images, put the exact copy in "quotes" and describe the typography.
  • Iterate with small changes: Make one adjustment at a time rather than rewriting everything.
  • Reference multiple images clearly: Label inputs by number when working with several references.

Inputs

  • prompt: What you want to generate or how to edit the input
  • input_images: One or more reference images (for editing or composing, up to 20)
  • aspect_ratio: 1:1, 3:2, 2:3, 16:9, or 9:16

Notes

GPT Image 2 does not support transparent backgrounds. Each call returns a single image at high quality.