GPT Image 2.6

Positioning Overview

gpt-image-2.6-sunburst is the text-to-image line within OpenAI's image generation model family, aimed at developers who need to produce images in batches through the unified HiAPI.ai interface. It supports generating images directly from text prompts, with output formats covering common raster images as well as SVG vector graphics and GIF animations, and finished-output specifications can be controlled through parameters such as quality, resolution, and aspect ratio. Among these, Sunburst better maintains image detail consistency across multiple rounds of iteration at medium and higher rendering quality, making it suitable for visual content workflows that require continuous output and repeated adjustment.

Key Highlights

• More stable detail consistency across rounds — when performing multiple rounds of generation or adjustment at medium or high rendering quality, Sunburst better maintains image detail consistency.
• Output formats extended to vector and animation — text-to-image can directly output SVG vector files and GIF animations, reducing the need for format conversion outside the interface.
• Generation and planning quality adjustable separately — quality controls rendering precision, while complexity independently controls the planning level, which can be raised separately for dense text and complex layouts.
• Aspect ratios cover common commercial layouts — aspect_ratio provides multiple ratios from 1:1 to 21:9 and 3:1, so the corresponding size can be produced in one go per distribution channel.

Capability Description

Text-to-image generation: enter a prompt of up to 32,000 characters to generate an image; the output defaults to png, suitable for scripted batch image generation.

Layered control of rendering quality and planning: quality offers five rendering precision levels from low to max, while complexity independently controls the planning level, so complex layouts can raise planning separately without having to raise the overall rendering tier.

Resolution and aspect ratio settings: resolution offers three tiers—1K, 2K, and 4K—and together with multiple aspect ratios, directly generates finished sizes that match the target layout.

Multi-format output and compression: png, jpeg, webp, gif, and svg are available; jpeg and webp support compression levels from 0 to 100, making it easy to trade off between image quality and file size.

Transparent background and GIF animation: when background is set to transparent, output is limited to png or webp; GIF allows setting frame count, frame size, and frame interval, with frame rate and frame dimensions determined directly by the parameters.

Use Cases

• Rapid draft generation for design teams — generate multiple draft versions from short prompts, filter by quality tier and aspect ratio, then move on to refinement, for comparing options at the concept stage.
• Continuous production of series brand visual assets — generate repeatedly around the same theme, with more stable details at medium-to-high quality; the output can be used directly for materials requiring a consistent style, such as official websites and product pages.
• Social and event materials for operations teams — generate accompanying images in batches at ratios such as 1:1, 9:16, and 16:9, then compress them for social media distribution and event landing pages.
• Vector and animation asset generation for developers — choose svg or gif output to directly obtain vector graphics or frame-by-frame animations, for icons, illustrations, and lightweight motion effects.

Limitations and Selection Advice

This line supports text-to-image generation only; if you need to make local modifications using an existing image as input, you should switch to the image-to-image line. Sunburst's cross-round consistency advantage is premised on medium or high rendering quality, and the same stability should not be expected at low quality tiers. GIF output does not support the aspect ratio parameter; frame size must be specified in pixels and must meet the frame count limit; transparent backgrounds are compatible only with png and webp. For scenarios with strict requirements on generation speed that do not need stable details, you can evaluate the Flare line in the same family.