AIモデル · openai
OpenAI GPT-Image 2.6 Flare
Fast text-and-image generation with controllable planning.
10 CR / RUN · openai · 10.6K RUNS
概要
gpt-image-2.6-flare is OpenAI’s fast image model for generating and editing images from both text and image inputs. It’s built for workflows where speed matters, without giving up control over how the model approaches a render.
A standout feature is its complexity setting, which lets you control how much the model plans before rendering. With support for aspect ratio, background, output format, multiple images, and frame-based outputs, it’s a flexible choice for everything from quick concepts to structured visual iterations.
強み
- 01Fast image generation and editing
- 02Works from text prompts and image inputs
- 03Complexity control for planning before render
- 04Supports aspect ratio and background options
- 05Can generate multiple images in one run
- 06Includes frame-based output settings
プロンプト例
Create a cinematic sci-fi city street at dusk with neon reflections, light rain, and a wide aspect ratio.
このプロンプトを試すEdit this product photo into a clean studio ad with a pure white background and soft commercial lighting.
このプロンプトを試すDesign a playful flat-vector travel poster of Lisbon with bold colors, simplified buildings, and crisp shapes.
このプロンプトを試すGenerate a short frame-based animation of a paper airplane gliding across a pastel sky, keeping the style minimal and cheerful.
このプロンプトを試す活用例
Rapid concept art
Turn text ideas into visuals quickly for moodboards, pitches, and early creative exploration. The model’s speed makes it useful for fast iteration.
Image-guided edits
Start from existing images and refine them with prompt-based changes. This is helpful for visual updates, style shifts, and controlled creative revisions.
Marketing visuals
Generate campaign imagery, product scenes, or social assets with control over background, format, and composition. Multiple output options support different publishing needs.
Simple motion sequences
Use frame count and frame duration settings to create frame-based visual sequences. It’s a practical option for lightweight animated concepts and experiments.
よくある質問
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