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SAVRN Model Hub · Comparisons

siglip2-base-patch16-256 vs siglip2-base-patch16-naflex

Siglip2-base-patch16-256 has 375M parameters and siglip2-base-patch16-naflex has 375M parameters; both are released under Apache License 2.0; at 16-bit, siglip2-base-patch16-256 needs about 0.9 GB (1x MI300X from $1.85 an hour) and siglip2-base-patch16-naflex about 0.9 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field siglip2-base-patch16-256
google/siglip2-base-patch16-256
siglip2-base-patch16-naflex
google/siglip2-base-patch16-naflex
Publisher Google Google
Task Zero shot image classification Zero shot image classification
Modality Other Other
Parameters, as reported 375M parameters 375M parameters
Architecture siglip Siglip2Model
Library transformers transformers
Context length Not stated Not stated
Repository size 1.5 GB 1.5 GB
Artifact formats safetensors safetensors
License apache-2.0 apache-2.0
Access Open weights, no gate Open weights, no gate
Memory at 16-bit (weights and margin) 0.9 GB 0.9 GB
Cheapest GPUs at 16-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Memory at 4-bit (weights and margin) 0.2 GB 0.2 GB
Cheapest GPUs at 4-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Revision viewed 3f9f96cb90da b53b807d3a2d
Downloads reported by the hub 3.9M 953.8k
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 siglip2-base-patch16-256

We would deploy this for one of the three jobs the publisher names: zero-shot image classification, image-text retrieval, or the vision encoder for a vision-language model. In 16-bit it wants 0.9 GB of memory for 0.8 GB of weights; 8-bit brings that to 0.5 GB. The cheapest setup on our list is one MI300X with 192 GB at $1.85 an hour, and at 375M parameters this model is a passenger on that card, not the reason to rent it.

Commercial use, modification and redistribution are permitted under Apache 2.0, with the license and NOTICE file kept and significant changes stated. Two things to check. No context length is recorded, so confirm the input limits against the three papers that describe it, arXiv:2502.14786, arXiv:2303.15343 and arXiv:2209.06794. And the weights arrive as safetensors only, 1.5 GB across 9 files, released February 17, 2025 and last updated four days later.

SAVRN's Notes on siglip2-base-patch16-naflex

Google built this encoder for three jobs: sorting images against text labels with no task-specific training, matching images to captions for retrieval, and serving as the vision tower inside a larger vision-language model. At 375 million parameters it needs 0.9 GB of memory at 16-bit precision, so hardware choice is about what else is on the card. The cheapest card in our table, one MI300X with 192 GB at $1.85 an hour on demand, carries it alongside the language model it feeds.

Apache 2.0 clears commercial use, modification and redistribution with the notices kept. Three papers describe the method, arXiv 2502.14786, 2303.15343 and 2209.06794, and the first titles it a multilingual vision-language encoder, which matters if your labels are not in English. The release is February 2025, so confirm your inference stack supports the siglip2 model type before ordering hardware.

Questions

Which is larger, siglip2-base-patch16-256 or siglip2-base-patch16-naflex?

siglip2-base-patch16-256 (375M parameters) is larger than siglip2-base-patch16-naflex (375M parameters), by the parameter counts their publishers report.

Which is cheaper to run, siglip2-base-patch16-256 or siglip2-base-patch16-naflex?

At 4-bit, siglip2-base-patch16-256 fits on 1x MI300X from $1.85 an hour and siglip2-base-patch16-naflex on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use siglip2-base-patch16-256 commercially?

Yes. siglip2-base-patch16-256 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 siglip2-base-patch16-naflex commercially?

Yes. siglip2-base-patch16-naflex 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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