SmolVLM - AI Vision Models Tool

Overview

SmolVLM is a 2B-parameter vision-language model optimized for small size, speed, and memory efficiency. Built on the Idefics3 architecture with improved visual compression and optimized patch processing, it supports local deployment (including laptops); all checkpoints, training recipes, and tools are released open-source under the Apache 2.0 license.

Key Features

• 2B-parameter vision-language model
• Improved visual compression strategy
• Optimized patch processing
• Small, fast, memory-efficient
• Suitable for local deployment on laptops
• Built on Idefics3 architecture
• All checkpoints, recipes, and tools are open-source
• Released under the Apache 2.0 license

Ideal Use Cases

• Research and experimentation with compact VLMs
• Local inference on laptops and edge devices
• Develop memory-efficient vision-language applications
• Reproduce or extend training recipes
• Education and model analysis with open checkpoints

Getting Started

• Visit the SmolVLM Hugging Face blog page
• Download model checkpoints, training recipes, and tools
• Clone the repository or download checkpoints locally
• Follow the provided README for training or inference
• Run inference locally using recommended hardware

Pricing

Open-source under Apache 2.0; no commercial pricing disclosed.

Key Information

• Category: Vision Models
• Type: AI Vision Models Tool