Google Research

ViT (Vision Transformer)

Transformer architecture applied to image recognition

ScalabilityStrong performance on vision tasksFoundation for multimodal vision

Where it ranks today

Best for / Not great for

Best for
  • Image classification
  • Object detection
  • Building blocks for more complex multimodal systems
Not great for
  • Direct text or audio processing
  • Generative tasks without additional components

Why it ranks here

The Vision Transformer demonstrated the power of the Transformer architecture for image-based tasks, paving the way for many subsequent multimodal models that blend vision with other modalities. It remains a key research component.

30-day trend

Score breakdown

Search trends85
Benchmarks88
Developer buzz87
News mentions84

Pricing

API: $0.00 in · $0.00 out per 1M tokens · Consumer: $0.00/mo

Pricing plans

Popular
Open Source Implementations
Access research code and pre-trained models
Free
  • Code available on platforms like GitHub
  • Various pre-trained checkpoints
  • Research papers for guidance
View on GitHub
Compare with another modelHow is this score calculated? →Snapshot 2026-06-27