How to use Nano AI Maker effectively
How to use Nano AI Maker effectively with the documented tools
Nano AI Maker works as a browser workspace for AI image generation, image editing, and short video creation. The most useful way to use it is to treat each task as a choice between a prompt, a reference image, and the model that best fits the result you want. The product is built around those inputs, so the main practical question is not whether it can make visuals, but which workflow matches the asset you need.
Start with the right input: prompt, reference image, or both
For fresh image generation, begin with a text prompt. Nano AI Maker supports text-to-image workflows, so you can describe the product shot, poster, editorial image, or social visual you want and then choose a model for the task.
When you already have source material, use a reference image instead. The documented workflows include image-to-image and reference-guided editing, which makes the source image the anchor for later changes. That is the right path when you want to restyle an existing image, keep the subject recognizable, or adapt one asset into a new version.
The same basic idea applies to video. Nano AI Maker supports text-to-video, image-to-video, and reference-to-video workflows, so a still image can become the starting point for a short clip when motion is the goal.
Choose the model based on the kind of output you need
Nano AI Maker includes multiple image and video models, and the model choice matters because the product is set up for different visual tasks rather than one fixed generation path. The homepage examples show product visuals, campaign art, character studies, reference edits, and motion drafts, which are all made from different model choices.
A practical way to read the interface is: first decide what kind of asset you need, then select a model for that task, then review the cost before submitting. That order matters because the model and settings determine both the output style and the credit cost.
Check the credit cost before you generate
Nano AI Maker uses credits per generation, and the generator shows the exact cost before you submit a request. That is the point where you can confirm whether you want a lower-cost quick concept run or a more expensive render.
The pricing page shows that credits are tied to the selected model and settings, with examples such as GPT Image 2 at different sizes and video credits that vary by model. The practical takeaway is simple: if you are testing directions, start with the cheapest documented option that fits the job, then move to a higher-cost run when the direction is set.
Use prompt editing when the change is about the image, not a new file
If you already have an image and want to change the background, lighting, or styling, Nano AI Maker supports text-based editing. That is useful when you want to preserve the subject while asking for a specific revision in everyday language.
The product also describes character consistency and scene preservation in reference-guided edits. In plain terms, that means you can ask for changes while keeping the main subject recognizable. This is the workflow to use when the image is already close to right and only needs a controlled revision.
Save the result path: preview, Activity, download
Completed image and video tasks are saved in Activity. That gives you a place to review finished work, track task status, and download the final image or playable video after generation succeeds.
For repeated visual work, this matters because you do not need to treat each generation as disposable. You can compare completed tasks, return to finished outputs, and keep the ones that are ready for use.
Use the product image resizer when the canvas needs to match the destination
Nano AI Maker also includes a browser-based product image resizer. It is useful when the asset already exists and the main job is preparing the right canvas for a listing, post, story, or card.
The resizer works locally in the browser and does not upload the source file. It supports square, portrait, story, landscape, and custom canvas sizes, and it exports PNG, JPG, or WebP. The key choice is between Cover and Contain:
- Cover fills the whole canvas and can crop edges. - Contain keeps the entire source image visible and adds empty space around it.
That makes the tool useful for publishing formats where framing matters more than changing the image itself. If the final destination has exact dimensions, the custom canvas option is there for that purpose. If the image must not be stretched, the resize workflow preserves aspect ratio.
Keep the export format aligned with the next use
For the resizer, JPG is suitable for photographs, PNG supports transparency, and WebP offers a smaller web image when the receiving site accepts it. The quality control applies to JPG and WebP, while PNG uses lossless canvas export.
A useful habit is to choose the output format according to where the file will go next, not just how it looks in the preview. That way the resized asset is ready for the platform or layout you plan to use.
Use the workspace for iteration, not only for the final render
Nano AI Maker is set up for quick creative testing as much as final output. The combination of multiple models, multiple output counts on supported image models, and saved Activity makes it practical to compare versions before settling on one.
If you are producing product visuals, campaign graphics, or short motion assets, the most effective sequence is usually: generate a first version, review it, refine the prompt or reference, and then save only the outputs that fit the brief.