OpenAI: GPT Image 2.5 Flare

GPT Image 2.5 Flare is an image generation and editing model from OpenAI. It sits within the GPT Image 2.5 series and is positioned as the speed oriented tier of that series, which makes it the variant aimed at high volume, everyday image work rather than the most demanding single outputs. If your workload involves producing or modifying images at a steady rate, this is the model in the family intended for that role.

The model takes text and images as input and produces images as output. Its context window is 400,000 tokens, with a maximum output of 360,000 tokens. Because it accepts image input as well as text, it can be used both for generating new images from a prompt and for editing or transforming images you supply. Generation is controlled through several image parameters. Aspect ratio is an enum with the values 1:1, 3:2, 2:3, 4:3, 3:4, 16:9, 9:16, 21:9 and auto. Quality is an enum with auto, low, medium, high, xhigh and max. Background is an enum with auto, transparent and opaque. The n parameter is a range from 1 to 10, input references range from 0 to 16, and output compression ranges from 0 to 100.

Those capabilities point to a fairly specific set of uses. High volume generation covers things like catalog or product imagery, social and marketing variants where you need many versions of a visual, and batch asset production where per image speed matters more than squeezing out the absolute best quality. The input references parameter, which accepts up to 16 images, supports editing and transformation workflows where the output should stay consistent with supplied visual material. Transparent background output is useful when images need to be composited onto other surfaces, and the compression range lets you trade file size against fidelity depending on where the image is going. The n range of up to 10 means a single request can return multiple candidates, which fits selection workflows where a person or a downstream step picks the best result.

You call the model through api14's OpenAI compatible API using the model id "openai/gpt-image-2.5-flare". Because the interface follows the OpenAI format, you can point an existing OpenAI client at api14 and change the model id rather than rewriting your integration. The request parameters it supports are max_tokens, response_format, seed and structured_outputs. The seed parameter is worth noting for reproducibility: passing the same seed lets you regenerate a result deterministically, which helps when you are testing prompts or need a stable output for a fixed input. The image specific controls listed above (aspect ratio, quality, background, n, input references and output compression) are passed alongside those parameters.

One practical consideration is the choice within the series. Flare is the speed oriented tier, so if a task demands the highest possible fidelity or the most complex editing, another model in the GPT Image 2.5 line may be the better fit. For repetitive, high volume work where throughput and cost efficiency per image dominate, this model is the appropriate default.