Image Classification is a fundamental task in computer vision that aims to assign a label or class to an entire image. The goal is to train a model that can recognize and categorize images into predefined classes.
1.28M training images, 50K validation images across 1,000 object classes. The standard benchmark for image classification since 2012.
Leading models on ImageNet-1K.
| # | Model | top-1-accuracy | Year | Source |
|---|---|---|---|---|
| ★ | CoCa (finetuned) | 91.0 | 2025 | paper ↗ |
| 2 | ViT-G/14 | 90.5 | 2025 | paper ↗ |
| 3 | SoViT-400m/14 | 90.3 | 2026 | paper ↗ |
| 4 | AIMv2-3B | 89.5 | 2026 | paper ↗ |
| 5 | AIMv2 ViT-3B/14 448px | 89.5 | 2024 | paper ↗ |
| 6 | BEiT-L+ | 89.5 | 2021 | paper ↗ |
| 7 | ConvNeXt V2 Huge | 88.9 | 2025 | paper ↗ |
| 8 | ALIGN | 88.6 | 2021 | paper ↗ |
| 9 | ViT-H/14 | 88.5 | 2025 | paper ↗ |
| 10 | Vision Transformer (ViT-H/14) | 88.5 | 2020 | paper ↗ |
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28 datasets tracked for this task.
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