ChatGPT from OpenAI
# GPT Image 2.5 Sunburst Advanced AI image generation for precise marketing. ## Overview GPT Image 2.5 Sunburst represents the pinnacle of OpenAI's image generation technology, specifically engineered for professional workflows where precision, text rendering, and instruction following are paramount. Unlike standard generative models that prioritize artistic flair over accuracy, Sunburst is designed to interpret complex prompts with high fidelity, ensuring that specific design requirements—such as brand-aligned color palettes, specific object placement, and legible typography—are met consistently. This model excels in both creation and iteration. Whether you are generating high-resolution assets from scratch or performing targeted edits on existing creative, Sunburst maintains structural integrity throughout the process. Its ability to handle complex spatial relationships and render sharp, readable text makes it an indispensable tool for ad agencies and marketing teams who require production-ready visuals without the need for extensive post-processing. ## Use Cases * Generating high-fidelity product mockups for social media ad campaigns. * Creating custom, brand-compliant typography and signage for digital billboards. * Iterative editing of existing ad assets to test different background environments or lighting conditions. * Rapid prototyping of visual concepts for marketing pitch decks and client presentations. * Generating consistent, photorealistic lifestyle imagery for e-commerce product pages. * Creating transparent-background assets for seamless integration into web design and landing pages. ## Parameters This model offers a robust suite of configuration options to fine-tune your output. Please refer to the Input Parameters section for details on controlling quality, aspect ratios, background transparency, and content moderation settings to ensure your generated assets meet specific project requirements. ## Tips for Best Results * Use specific, descriptive language when defining text elements to leverage the model's superior rendering capabilities. * For complex compositions, start with a lower quality setting to iterate on the layout, then switch to 'max' for the final render. * Utilize the 'transparent' background setting when creating assets intended for layering in Photoshop or other design software. * When providing reference images, ensure they are high-resolution to help the model better understand the style and structural cues. * Experiment with the 'auto' aspect ratio if you are unsure of the final placement, but lock it to a specific ratio for consistent campaign assets. * Use the moderation 'auto' setting for standard commercial projects to ensure compliance with safety guidelines. ## About GPT Image 2.5 Sunburst is developed by OpenAI and optimized for the Pixloop platform. As the latest iteration in the GPT-Image lineage, it builds upon years of research into latent diffusion models and instruction-tuned visual synthesis. It is designed to bridge the gap between creative exploration and professional production, providing a reliable, high-performance engine for modern digital advertising.
Model input reference derived from preset schema.
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
| prompt | string | Yes | null | A text description of the desired image |
| quality | select | No | "low" | The quality of the generated image. Higher quality takes longer and costs more. |
| user_id | string | No | null | An optional unique identifier representing your end-user. This helps OpenAI monitor and detect abuse. |
| background | select | No | "auto" | Set whether the background is transparent or opaque or choose automatically |
| moderation | select | No | "auto" | Content moderation level |
| aspect_ratio | select | No | "1:1" | The size of the generated image. Use 'auto' to let the model pick. Sizes above 2560x1440 are experimental and may give more variable results. |
| input_images | image | No | [] | A list of images to use as input for the generation |
| output_format | select | No | "png" | Output format |
| number_of_images | integer | No | 1 | Number of images to generate (1-10) |
| output_compression | integer | No | 90 | Compression level (0-100%) |