microsoft/Phi-3.5-vision-instruct
microsoft/Phi-3.5-vision-instruct is a 4.1 billion parameter open multimodal model developed by Microsoft, featuring a 128K token context length. It is designed for general-purpose AI systems requiring both visual and text input, excelling in memory/compute constrained environments and latency-bound scenarios. This model is particularly strong in general image understanding, OCR, chart/table understanding, and multi-image reasoning, including summarization and comparison.
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Overview
microsoft/Phi-3.5-vision-instruct is a 4.1 billion parameter open multimodal model from Microsoft's Phi-3 family, capable of processing both text and image inputs with a 128K token context length. It was trained on a diverse dataset including synthetic data, filtered public websites, and high-quality reasoning-dense data for both text and vision. The model underwent supervised fine-tuning and direct preference optimization for instruction adherence and safety. A recent update enhanced its multi-frame image understanding, improving performance on benchmarks like MMMU, MMBench, and TextVQA.
Key Capabilities
- Multimodal Input: Processes both text and multiple images.
- Extended Context: Supports a 128K token context length for comprehensive understanding.
- Multi-frame Reasoning: Excels at detailed image comparison, multi-image summarization, and video summarization.
- Document Intelligence: Strong performance in optical character recognition (OCR) and chart/table understanding.
- Optimized Performance: Designed for memory/compute constrained and latency-bound environments.
Good For
- General image understanding and analysis.
- Applications requiring optical character recognition (OCR).
- Interpreting and extracting information from charts, tables, and diagrams.
- Comparing and reasoning across multiple images or video clips.
- Developing AI systems where computational resources or response times are critical.