Identify what your image shows with MobileViT-Small — a lightweight vision model trained on 1000 ImageNet classes. Top-5 predictions with confidence bars. Runs entirely in your browser.
Your images never leave your device. Classification happens locally.
Drop image here or click to select
PNG, JPG, WebP — any image
Runs entirely in your browser. Your data never leaves your device.
Tested on ImageNet validation split — average classification time 0.8s on MacBook Air M2.
| Metric | Value |
|---|---|
| Model size (INT8) | ~18MB |
| Parameters | ~5M |
| Avg inference time | 0.8s / image |
| Model load (cold start) | ~6s (CDN) / <1s (cached) |
| ImageNet-1k Top-1 Accuracy | 76.7% |
| ImageNet-1k Top-5 Accuracy | 93.0% |
Last verified: September 2026.
No. This AI image classifier runs entirely in your browser using WebAssembly. Images are processed locally with MobileViT-Small and never leave your device.
MobileViT-Small is trained on ImageNet-1k, so it can classify images into 1000 different categories including dogs, cats, cars, planes, flowers, insects, household objects, and many more.
A classifier identifies what the image is (top-5 labels). An object detector finds and locates multiple objects with bounding boxes. Our AI Object Detector does the latter — use it when you need exact object positions.
ImageNet-1k has very specific labels. A photo of a cute mixed-breed dog might score low on 'golden retriever' because it is not a pure example. Lower confidence = more ambiguous image or unfamiliar category.