OpenAI: GPT-5 Image Mini

GPT-5 Image Mini is an OpenAI model that blends the company's language capabilities with image generation. OpenAI describes it as combining the language abilities of GPT-5 Mini with GPT Image 1 Mini, which is where the "mini" in the name comes from: it is the smaller, more efficient member of the GPT-5 Image family rather than the largest. It sits in the image category but is also classified as a text model, so it is best understood as a natively multimodal system that handles both directions of work in one place.

On the input side the model accepts text, images and files, and on the output side it returns both image and text. That means the same request can carry a written prompt and reference images, and the reply can contain generated imagery plus written content. The context window is 400,000 tokens, which is large enough to hold long prompts, extended conversations and multiple references at once. Maximum output is 128,000 tokens. Image generation is configurable: aspect ratio supports 1:1, 3:2, 2:3 and auto; quality supports auto, low, medium and high; background supports auto, transparent and opaque; you can request between 1 and 10 images per call; up to 16 input references; and output compression is adjustable from 0 to 100.

Those capabilities point to a fairly wide set of practical uses. Because the model takes reference images alongside text, it suits tasks where a written instruction must be applied to existing visual material, such as producing variations of a supplied image or generating assets that follow a described style. Transparent background support is useful when output needs to be composited into a design or interface rather than used as a standalone picture, and the aspect ratio options cover square, landscape and portrait formats. On the text side, the large context and long maximum output make it viable for longer documents or reasoning-heavy requests that also produce visuals. The quality setting lets you trade generation effort against speed depending on the task.

You call the model through api14's OpenAI-compatible API using the model id "openai/gpt-5-image-mini". The supported parameters are include_reasoning, logprobs, max_tokens, reasoning, response_format, seed, structured_outputs, temperature, top_logprobs, top_p and verbosity. The image controls (aspect ratio, quality, background, image count, input references and output compression) are passed as part of the request alongside those parameters. Because structured_outputs and response_format are available, you can constrain text responses to a schema, and seed allows reproducible sampling when you need consistent results across runs.

The main thing to weigh is that this is the mini variant: if a task demands the strongest possible image generation or the most capable language reasoning, the larger GPT-5 Image model is the more natural fit. GPT-5 Image Mini is aimed at efficiency, so it makes sense when throughput, cost control or latency matter more than maximum quality. It is a reasonable default for high-volume generation, reference-driven editing and mixed text-and-image responses, and it is worth testing against your own prompts before committing to it for anything where output quality is critical.