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SAVRN Model Hub · Comparisons

dinov2-base vs vit-base-patch16-224-in21k

Dinov2-base has 87M parameters and vit-base-patch16-224-in21k has 86M parameters; both are released under Apache License 2.0; at 16-bit, dinov2-base needs about 0.2 GB (1x MI300X from $1.85 an hour) and vit-base-patch16-224-in21k about 0.2 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field dinov2-base
facebook/dinov2-base
vit-base-patch16-224-in21k
google/vit-base-patch16-224-in21k
Publisher AI at Meta Google
Task Image feature extraction Image feature extraction
Modality Other Other
Parameters, as reported 87M parameters 86M parameters
Architecture Dinov2Model ViTModel
Library transformers transformers
Context length Not stated Not stated
Repository size 692.7 MB 1.4 GB
Artifact formats safetensors, pytorch safetensors, pytorch, jax, tf
License apache-2.0 apache-2.0
Access Open weights, no gate Open weights, no gate
Memory at 16-bit (weights and margin) 0.2 GB 0.2 GB
Cheapest GPUs at 16-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Memory at 4-bit (weights and margin) 0.1 GB 0.1 GB
Cheapest GPUs at 4-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Revision viewed f9e44c814b77 b4569560a39a
Downloads reported by the hub 3.4M 1.8M
Last observed 2026-09-18 2026-09-18

An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.

SAVRN's Notes on dinov2-base

Nothing about this one strains a card. The 16-bit weights load in 0.2 GB, and the cheapest option on the page is one MI300X with 192 GB at $1.85 an hour, so share the card; the image batch sets the bill, not the encoder. What comes out is a feature vector, not an answer, which puts its 87M parameters and 768-wide hidden state ahead of your own classifier or retrieval index.

Nothing in the license slows a deployment: Apache 2.0 covers commercial use, modification and redistribution as long as the notices stay attached, so a fine-tuned head ships with the encoder in a product. Two things to confirm: the page lists no reported evaluations, so your own held-out images are the benchmark, and the publisher's team did not write the model card, so the paper it cites, arXiv:2304.07193, is the record of training. Weights last updated January 17, 2024.

SAVRN's Notes on vit-base-patch16-224-in21k

Released in March 2022, this one does image feature extraction: 86M parameters, pre-trained on ImageNet-21k at 224 by 224, 14 million images across 21,843 classes. Memory is a non-issue at 0.2 GB in 16-bit, and 4-bit weights round to 0.0 GB, so skip quantizing. The cheapest Index setup, one MI300X with 192 GB at $1.85 an hour on demand, bills by the hour, so throughput, not fit, is the whole question.

Apache 2.0 covers commercial use, modification and redistribution with a patent grant; keep the notices and state significant changes. There is no context length and no host token price on the Index, since it produces features, not tokens. The weights ship in safetensors, pytorch, jax and tf, and the releasing team did not write the model card, so the paper, An Image is Worth 16x16 Words, is the reference to read before you wire it in.

Questions

Which is larger, dinov2-base or vit-base-patch16-224-in21k?

dinov2-base (87M parameters) is larger than vit-base-patch16-224-in21k (86M parameters), by the parameter counts their publishers report.

Which is cheaper to run, dinov2-base or vit-base-patch16-224-in21k?

At 4-bit, dinov2-base fits on 1x MI300X from $1.85 an hour and vit-base-patch16-224-in21k on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use dinov2-base commercially?

Yes. dinov2-base is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

Can I use vit-base-patch16-224-in21k commercially?

Yes. vit-base-patch16-224-in21k is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

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