What are the hardware requirements for SmolVLM Synthetic?

SmolVLM Synthetic requires approximately 4.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SmolVLM Synthetic and how large is it?

SmolVLM Synthetic is developed by HuggingFaceTB, a model with 1.7b 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 SmolVLM Synthetic?

SmolVLM Synthetic is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmolVLM Synthetic by HuggingFaceTB — VRAM 4.5GB

Name: SmolVLM Synthetic
Author: HuggingFaceTB

SmolVLM Synthetic is an open-source language model by HuggingFaceTB. Features: 1.7b LLM, VRAM: 4.5GB, License: apache-2.0.

Base model:finetune:huggingfac... Base model:huggingfacetb/smoll... Conversational Dataset:huggingfacem4/docmatix Dataset:huggingfacem4/the caul... En Endpoints compatible Idefics3 Image-text-to-text Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/HuggingFaceTB/SmolVLM-Synthetic

SmolVLM Synthetic Parameters and Internals

LLM Name	SmolVLM Synthetic
Repository 🤗	https://huggingface.co/HuggingFaceTB/SmolVLM-Synthetic
Base Model(s)	HuggingFaceTB/SmolLM2-1.7B-Instruct google/siglip-so400m-patch14-384 HuggingFaceTB/SmolLM2-1.7B-Instruct google/siglip-so400m-patch14-384
Model Size	1.7b
Required VRAM	4.5 GB
Updated	2026-08-09
Maintainer	HuggingFaceTB
Model Type	idefics3
Model Files	4.5 GB
Supported Languages	en
Model Architecture	Idefics3ForConditionalGeneration
License	apache-2.0
Model Max Length	16384
Transformers Version	4.46.0
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49155
Torch Data Type	bfloat16

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Instruction Following and Task Automation
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Data Analysis and Insight Generation
Text Generation
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Multi-Language Support and Translation

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