Classification Model Rankings
Updated Aug 26Browse the leading AI models for image classification. See how models rank for accuracy, latency, and real-world performance.
ELO ratings for the highest performing models
ELO score vs average latency • Better models are top-left
| Action | |||||||
|---|---|---|---|---|---|---|---|
1 | multimodal | 1224 | 5 | 3.69s | |||
2 | multimodal | 1215 | 5 | 2.02s | |||
3 | multimodal | 1215 | 5 | 7.34s | |||
4 | multimodal | 1212 | 4 | 8.01s | OpenAI | ||
5 | multimodal | 1212 | 5 | 2.48s | OpenAI | ||
6 | multimodal | 1212 | 5 | 6.87s | OpenAI | ||
7 | multimodal | 1212 | 5 | 2.18s | Anthropic | ||
8 | multimodal | 1212 | 5 | 5.45s | OpenAI | ||
9 | multimodal | 1211 | 5 | 2.72s | OpenAI | ||
10 | multimodal | 1211 | 5 | 3.18s | |||
11 | multimodal | 1200 | 5 | 3.50s | |||
12 | multimodal | 1200 | 5 | 2.43s | Anthropic | ||
13 | multimodal | 1200 | 3 | 5.55s | Anthropic | ||
14 | multimodal | 1200 | 5 | 2.92s | Anthropic | ||
15 | multimodal | 1200 | 5 | 4.09s | Anthropic | ||
16 | multimodal | 1200 | 5 | 864ms | |||
17 | multimodal | 1200 | 5 | 7.60s | OpenAI | ||
18 | multimodal | 1200 | 5 | 4.36s | OpenAI | ||
19 | multimodal | 1200 | 5 | 3.15s | OpenAI | ||
20 | multimodal | 1189 | 5 | 2.33s | Anthropic | ||
21 | multimodal | 1188 | 2 | 4.25s | |||
22 | multimodal | 1188 | 5 | 3.33s | OpenAI | ||
23 | multimodal | 1188 | 5 | 2.76s | OpenAI | ||
24 | multimodal | 1166 | 5 | 3.41s | Anthropic |
What is Classification?
Image classification is the task of assigning category labels to an image based on its content. Given a photo, a model outputs which categories are present and how confident it is in each one. Unlike object detection, it doesn't tell you where in the image something appears. Just whether it's there.
You define the classes you want to test. Type in your categories, run the models, and each one returns a confidence score per class. This makes it easy to evaluate how different models handle your specific label set without writing any code.
Rankings on this page are based on ELO scores from head-to-head battles in the Classification Arena, run on real tasks submitted by users.
Frequently Asked Questions
Routing documents by type, filtering and moderating content at scale, categorizing products in e-commerce catalogs, quality control in manufacturing, and triaging images by category before review.
Healthcare for diagnostic image sorting, retail for product cataloging, finance and insurance for document classification, manufacturing for defect categorization, and media platforms for content moderation.
Classification tells you which categories are present in an image and how confident the model is for each one. Object detection also locates where each object appears by drawing a bounding box around it.
No. You define the classes you want to test, run the models, and get confidence scores back immediately. For production use on a specific, narrow class set, fine-tuned models typically outperform general-purpose ones.
Rankings are based on ELO scores from head-to-head battles in the Classification Arena. Users vote on which model's confidence scores best reflect the actual content of the image.
Yes. Open the Classification Playground, select the models you want to compare, upload an image, and enter the classes you want to test.