OpenAI GPT Image 2 Image Model

GPT Image 2 (`gpt-image-2`) is OpenAI's state-of-the-art image generation and editing model. In UGC Copilot it is the second image engine, selectable alongside the default Gemini image stack ("Nano Banana"), and powers AI persona portraits, product composites, scene images, and scene edits.

What makes GPT Image 2 different

GPT Image 2 is strongest at photorealism and instruction following — it renders human hands, faces, and product labels with fewer artifacts than most image models, and its native editing endpoint accepts multiple reference images in one request. That matters for UGC ads: UGC Copilot passes your product photo (and your creator's reference image) directly into the generation call, so the exact product — shape, label, logo, and text — appears in the composite instead of an AI's approximation of it.

How UGC Copilot uses it

Pick GPT Image in the image-engine selector on the Create step and every persona, product composite, scene image, and edit in that project routes through GPT Image 2. Quality maps to two tiers: Standard (1 credit, OpenAI's `medium` quality) and HQ (3 credits, `high` quality). The Gemini engine remains the default at 1 credit standard / 2 credits HQ.

One technical detail handled for you: GPT Image 2 natively renders square (1:1), portrait (2:3), and landscape (3:2) frames rather than true vertical 9:16. UGC Copilot generates at the closest frame and center-crops server-side to exact 9:16 (or whichever ratio you chose), because scene images feed video engines like Veo 3.1 and Kling 3.0 as literal start frames where the aspect ratio must match precisely.

When to choose GPT Image 2 vs Gemini

Reach for GPT Image 2 when product fidelity and realism matter most — beauty and skincare composites, packaged goods where the label must read correctly, or hero persona shots. It is slower (complex prompts can take up to ~2 minutes) and HQ costs one credit more than Gemini HQ. Stick with the Gemini default for fast iteration and native vertical framing — it renders true 9:16 with no crop and returns in seconds. Every image, on either engine, passes through the same automated quality-control loop that checks anatomy and composition before you see it.

Frequently Asked Questions

What is GPT Image 2 used for in UGC Copilot?
GPT Image 2 is a selectable image engine for AI persona portraits, product composites, scene images, and scene edits. Pick "GPT Image" in the engine selector on the Create step and every image in that project routes through OpenAI's gpt-image-2 model instead of the default Gemini stack. It costs 1 credit for standard quality and 3 credits for HQ (Gemini is 1/2).
Is GPT Image 2 better than Gemini for product images?
For product fidelity, usually yes. GPT Image 2 accepts your product photo as a direct edit reference and is notably strong at preserving labels, logos, and printed text, so packaged goods read correctly in composites. Gemini ("Nano Banana") remains the better default for speed and native 9:16 vertical framing — GPT Image 2 output is center-cropped to 9:16 server-side.
Why is GPT Image 2 HQ more expensive than Gemini HQ?
Provider cost. OpenAI bills GPT Image 2 by output tokens, and a high-quality vertical image costs roughly 10× a medium-quality one at the API level. UGC Copilot prices GPT standard at 1 credit (same as Gemini) and GPT HQ at 3 credits versus Gemini HQ's 2 — the extra credit reflects the underlying model cost, not a markup on quality alone.
How long does GPT Image 2 take to generate an image?
Typically 20–60 seconds, and up to about 2 minutes for complex composite prompts — noticeably slower than Gemini, which usually returns in seconds. Every generation on either engine also passes an automated quality-control check (anatomy, composition, product accuracy) with one automatic retry, and you are charged once regardless of internal retries.

Related Terms

Nano Banana ProAI PersonaAI Video Generation
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