dinov3-vits16-pretrain-lvd1689m
by facebook
DINOv3 at 21.6M parameters, small enough to run over everything
facebook/dinov3-vits16-pretrain-lvd1689mOverview
The smallest DINOv3 checkpoint, distilled from the same 7B teacher as the larger ones. Self-supervised, no text tower, so it groups images by how they look rather than by what a caption would say about them.
Size is the whole argument here. At 21.6M parameters this runs over an entire image library on hardware that would choke on the ViT-B, which makes it the right first pass for deduplication and near-duplicate detection where you need to touch every file rather than a sample.
Use a larger checkpoint when precision on hard pairs matters more than covering the corpus.
Architecture
Vision transformer, patch size 16, DINOv3ViTModel with 21,596,544 parameters. Self-supervised training on LVD-1689M, distilled from the 7B teacher. Image-feature-extraction only: no text encoder, so it cannot answer a text query on its own.
Key Capabilities
- •Dense visual features at a size that scales to whole archives
- •Near-duplicate detection without labels
- •Frame-level features for clustering unlabelled footage
- •A cheap first pass ahead of a larger visual encoder
Use Cases on Mixpeek
- •Deduplicating a large image library where a bigger model is unaffordable per file
- •Reverse image search over object storage
- •Clustering an archive before anyone has written a taxonomy
- •Screening candidates for a more expensive encoder to rerank
Tags
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Open StudioHow It Runs on Mixpeek
On Mixpeek, dinov3-vits16-pretrain-lvd1689m runs as a managed extractor inside a processing pipeline. Point a bucket of image feature extraction data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.
Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.
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Specification
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