DINOv3 ViT-L/16
Parameters
300M
Context Length
-
Modality
Text
Architecture
-
License
other
Release Date
6 Aug 2025
Knowledge Cutoff
-
API Pricing (per 1M)
Self-hosted only
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
131,072 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for DINOv3 ViT-L/16 available.
Rankings
Overall Rank
-
Coding Rank
-
About DINOv3 ViT-L/16
DINOv3 ViT-L/16 is a self-supervised vision transformer foundation model pretrained on large-scale visual data by Meta. It extracts robust semantic representations useful across dense visual downstream tasks.
Technical Specifications
Attention
Attention Structure
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Attention Heads
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Key-Value Heads
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Attention Head Dimension
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Position Embedding
-
RoPE Theta
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Sliding Window Attention
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Sliding Window Size
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Sliding Window Ratio
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Linear Attention
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Linear Attention Ratio
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Normalization
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Activation Function
-
Dimensions
Auxiliary Parameters
-
Hidden Dimension Size
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Number of Layers
-
FFN Intermediate Size (Dense)
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Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
-
Resources
About DINO
The DINO model family developed by Meta.
Other DINO Models
- No related models available