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Moondream 2b 2025 04 14 4bit

Developed by moondream
Moondream is a lightweight vision-language model designed for efficient cross-platform deployment. The 4-bit quantized version released on April 14, 2025 significantly reduces memory usage while maintaining high accuracy.
Downloads 6,037
Release Time : 5/20/2025

Model Overview

Moondream is an efficient vision-language model capable of handling tasks such as image-text generation, visual question answering, object detection, and localization tagging. Its 4-bit quantized version achieves substantial memory reduction through quantization-aware training techniques.

Model Features

Efficient Quantization
Utilizes 4-bit quantization technology, reducing memory usage by 42% with only a 0.6% accuracy drop
Cross-Platform Compatibility
Designed for efficient operation across various hardware platforms
Multi-Task Support
Supports multiple tasks including image captioning, visual question answering, object detection, and localization tagging
High-Speed Inference
Achieves generation speed of 184 tokens/second on Nvidia RTX 3090

Model Capabilities

Image Captioning
Visual Question Answering
Object Detection
Localization Tagging
Streaming Generation

Use Cases

Image Understanding
Automatic Image Tagging
Generates short or standard-length descriptive text for images
Can produce image descriptions of varying lengths
Visual QA System
Answers natural language questions about image content
Accurately answers questions like 'How many people are in the picture?'
Computer Vision
Object Detection
Detects specific objects in images
Can detect specific objects like human faces
Localization Tagging
Marks positions of specific objects in images
Can tag locations of objects like people
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