GPT Image 2 is now available on vevaro. You can use it for both text-to-image generation and image-to-image editing inside the studio, with real controls for quality, aspect ratio, and output format so testing and production feel much more flexible.
This launch matters because GPT Image 2 now gives creators, marketers, and design teams a cleaner prompt-first image workflow plus real controls for quality, aspect ratio, and output format. If you want to generate a new concept from text or transform an existing image with a reference-driven edit, GPT Image 2 is now ready to use on vevaro.
GPT Image 2 brings two practical workflows into one release on vevaro. The first is GPT Image 2 text to image, which turns prompts into finished visuals. The second is GPT Image 2 image to image, which lets you upload a reference image and describe the transformation you want.
On vevaro, this model now runs with fal, which means GPT Image 2 also exposes the controls people actually need in production: image size, quality, and output format. That combination makes GPT Image 2 especially useful for creative iteration. You can start with a concept prompt, generate a first image, then move into editing to refine layout, product styling, background treatment, color direction, or campaign-specific variations.
On the create side, GPT Image 2 supports prompt-driven generation with adjustable quality, supported aspect ratios, and PNG, JPEG, or WebP output. That gives you more control over how you test ideas and how you prepare finished assets for different workflows.
Instead of treating every generation the same, you can use lower-cost quality settings for ideation and move to higher quality when a concept is ready. That makes GPT Image 2 a strong option for social graphics, concept visuals, ad mockups, thumbnails, editorial illustrations, and brand experiments.
On the edit side, GPT Image 2 supports reference-based image editing. Upload an image, describe the new scene or change you want, and vevaro sends it through the GPT Image 2 image-to-image workflow with the same quality and format controls available in generation mode.
This is a strong fit for creators who already have source material and want cleaner iteration loops. Instead of rebuilding a scene from scratch every time, you can keep the reference and direct the edit with prompt changes. That makes GPT Image 2 useful for product refreshes, ad variants, set extensions, style shifts, and creative direction changes.
GPT Image 2 on vevaro now uses quality-based pricing. Low quality starts at 10 credits for fast ideation, medium quality is 42 credits as the balanced default for everyday work, and high quality is 120 credits for premium outputs and more demanding prompt tests.
That structure fits how most teams actually work. You can iterate cheaply at the start of a creative brief, then switch to higher quality only for the versions that matter. It keeps pricing predictable on-platform while still giving you a more reasonable margin than a one-price-fits-all model.
GPT Image 2 fits especially well when the prompt is doing the heavy lifting. Product marketing teams can use it for hero concepts, seasonal variations, and e-commerce posters. Social teams can use it for campaign art, thumbnails, quote-card backgrounds, and fast visual ideation.
It is also a good model for creative agencies and solo designers who want to move from rough concepting into polished exploration without switching platforms. Generate an idea, edit the winning frame, then keep iterating inside the same studio workflow.
A strong workflow on vevaro is to begin with GPT Image 2 text to image for broad exploration. Write three to five different prompt directions for the same brief and generate a first batch. Once one direction feels promising, send that visual into GPT Image 2 edit mode and refine from there.
This approach reduces prompt drift and helps you stay anchored to a visual direction that already works. It is especially effective for ad creatives, landing page visuals, app store screenshots, poster concepts, and visual storytelling experiments.
The best GPT Image 2 prompts are specific about subject, composition, lighting, setting, and finish. Instead of writing "make a shoe ad," describe the scene in a way that gives the model clear visual intent: subject, camera framing, background, material feel, color palette, and overall mood.
For example, a stronger prompt would be: "Premium running shoe hero image on a reflective black platform, dramatic side lighting, floating dust particles, shallow depth of field, dark studio background, luxury sportswear campaign look."
For editing, describe the change clearly instead of re-describing the full image. If the reference already contains the main subject, focus your prompt on the transformation: change the environment, restyle the wardrobe, shift the color story, replace the background, or turn the composition into a polished poster.
There is a big difference between a model that looks interesting on paper and a model that is wired into a usable workflow. GPT Image 2 matters on vevaro because it is available in both create and edit flows, so you can move from concept generation to guided refinement without breaking your process.
That makes this launch more than a simple model checkbox. It gives users a practical new option for image generation and editing inside a studio that already supports multi-model workflows.
If you want a prompt-first image model with real controls for quality, aspect ratio, and output format, GPT Image 2 is now live on vevaro. Open Create Image to generate from scratch, or open Edit Image to transform a reference image with the same model family.
The fastest way to evaluate it is simple: generate a concept, pick the best frame, then run one or two targeted edit passes. That gives you a realistic feel for how GPT Image 2 performs in a real creative workflow instead of a single isolated prompt test.
Generate new images or edit a reference image with GPT Image 2 inside vevaro.
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