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openai/gpt-image-2.6-flareRuns on your balance at the prices above. New accounts start with free usage.
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GPT Image 2.6 Flare is an image generation and editing model from OpenAI. It sits in the image category and is built for speed, targeting fast iteration and interactive workflows rather than slower batch-style production. If your pipeline depends on quick turnaround between a prompt and a usable image, this is the model OpenAI positions for that job.
The model accepts text and image inputs and produces image outputs. Its context window is 400,000 tokens, with a maximum output of 360,000 tokens. Image generation is controlled through a set of dedicated parameters: aspect ratio (1:1, 3:2, 2:3, 4:3, 3:4, 16:9, 9:16, 21:9, or auto), output format (png, jpeg, or webp), quality (auto, low, medium, high, xhigh, or max), and background (auto, transparent, or opaque). You can request between 1 and 10 images per call with n, supply up to 16 input references, and set output compression anywhere from 0 to 100.
Those capabilities point to a few practical patterns. Text to image covers concept exploration, marketing visuals, and placeholder art where you want to try many directions quickly. Image to image with up to 16 references suits editing, restyling, and composition work where existing assets need to guide the result. Transparent backgrounds and webp or png output fit straight into web and app asset pipelines, and the quality and compression controls let you trade fidelity against file size per request. Requesting several images at once with n is useful when you want variants to compare side by side.
You call the model through api14's OpenAI-compatible API using the model id "openai/gpt-image-2.6-flare". Because the interface follows the OpenAI schema, existing OpenAI client libraries and request shapes carry over with minimal change. The supported request parameters are max_tokens, response_format, seed, and structured_outputs, alongside the image parameters described above. The seed parameter helps you reproduce a result you liked, and structured_outputs lets you constrain responses in a structured form.
The model is optimized for speed, so it fits interactive and iterative work best. If your workload is dominated by very large volumes of images or by workflows where latency is not the constraint, compare it against other image models on the gateway before committing. The parameter set is focused on image generation and editing; there is no separate text output mode to plan around.
%3B%0A%0Aconst%20result%20%3D%20await%20client.images.generate(%7B%0A%20%20%22model%22%3A%20%22openai%2Fgpt-image-2.6-flare%22%2C%0A%20%20%22prompt%22%3A%20%22A%20minimalist%20product%20photo%20of%20a%20ceramic%20mug%20on%20a%20wooden%20table%22%2C%0A%20%20%22n%22%3A%201%2C%0A%20%20%22aspect_ratio%22%3A%20%221%3A1%22%0A%7D)%3B%0Aimport%20%7B%20writeFile%20%7D%20from%20%22node%3Afs%2Fpromises%22%3B%0Aawait%20writeFile(%22image.png%22%2C%20Buffer.from(result.data%5B0%5D.b64_json%2C%20%22base64%22))%3B%0A){kind=link}
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.images.generate({
"model": "openai/gpt-image-2.6-flare",
"prompt": "A minimalist product photo of a ceramic mug on a wooden table",
"n": 1,
"aspect_ratio": "1:1"
});
import { writeFile } from "node:fs/promises";
await writeFile("image.png", Buffer.from(result.data[0].b64_json, "base64"));
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