Phi-3.5-vision-instruct
| Property | Value |
|---|---|
| Parameter Count | 4.15B |
| Context Length | 128K tokens |
| License | MIT |
| Paper | Technical Report |
| Architecture | Vision-Language Model with Flash Attention |
What is Phi-3.5-vision-instruct?
Phi-3.5-vision-instruct is a state-of-the-art multimodal AI model developed by Microsoft that combines advanced vision and language capabilities. This lightweight model supports both image and text processing with an impressive 128K token context length, making it suitable for complex multimodal tasks and extended conversations.
Implementation Details
The model architecture consists of an image encoder, connector, projector, and the Phi-3 Mini language model, totaling 4.15B parameters. It's trained on 500B tokens of combined vision and text data, using 256 A100-80G GPUs over 6 days.
- Supports multiple input formats including single image, multi-image, and conversational interactions
- Implements Flash Attention 2 for optimal performance
- Trained on high-quality, filtered datasets including synthetic data and public websites
Core Capabilities
- General image understanding and OCR
- Chart and table comprehension
- Multiple image comparison and analysis
- Video clip summarization
- Multilingual support (primarily optimized for English)
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its efficient architecture and strong performance on multi-frame capabilities, outperforming competitors of similar size on benchmarks like BLINK and Video-MME. It achieves this while maintaining a relatively small parameter count of 4.15B.
Q: What are the recommended use cases?
The model is ideal for memory/compute constrained environments, latency-bound scenarios, and applications requiring general image understanding, document processing, and multi-image analysis. It's particularly well-suited for commercial and research applications requiring efficient multimodal processing.
