What are the hardware requirements for Siglip2 Base Patch16 512?

Siglip2 Base Patch16 512 requires approximately 1.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Siglip2 Base Patch16 512 and how large is it?

Siglip2 Base Patch16 512 is developed by google, a model with 375.8m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Siglip2 Base Patch16 512?

Siglip2 Base Patch16 512 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Siglip2 Base Patch16 512 by google — VRAM 1.5GB

Name: Siglip2 Base Patch16 512
Author: google

Siglip2 Base Patch16 512 is an open-source language model by google. Features: 375.8m LLM, VRAM: 1.5GB, License: apache-2.0.

Arxiv:2209.06794 Arxiv:2303.15343 Arxiv:2502.14786 Endpoints compatible Region:us Safetensors Siglip Vision Zero-shot-image-classification

Model Card on HF 🤗: https://huggingface.co/google/siglip2-base-patch16-512

Siglip2 Base Patch16 512 Parameters and Internals

LLM Name	Siglip2 Base Patch16 512
Repository 🤗	https://huggingface.co/google/siglip2-base-patch16-512
Model Size	375.8m
Required VRAM	1.5 GB
Updated	2026-08-09
Maintainer	google
Model Type	siglip
Model Files	1.5 GB
Model Architecture	AutoModel
License	apache-2.0
Transformers Version	4.49.0.dev0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation