Phi-4-multimodal-instruct
| Property | Value |
|---|---|
| Parameters | 5.6B |
| Context Length | 128K tokens |
| License | MIT |
| Author | Microsoft |
| Release Date | February 2025 |
What is Phi-4-multimodal-instruct?
Phi-4-multimodal-instruct is Microsoft's latest lightweight multimodal foundation model that can process text, images, and audio inputs. Built upon the research from Phi-3.5 and 4.0 models, it represents a significant advancement in multimodal AI capabilities, supporting 23 languages for text, English for vision, and 8 languages for audio processing.
Implementation Details
The model utilizes a sophisticated architecture combining supervised fine-tuning, direct preference optimization, and RLHF for enhanced instruction adherence and safety. It requires specific GPU hardware (NVIDIA A100, A6000, or H100) for optimal performance using flash attention, though it can run on older GPUs using eager attention implementation.
- Training involved 512 A100-80G GPUs over 28 days
- Processed 5T tokens, 2.3M speech hours, and 1.1T image-text tokens
- Implements advanced encoders and adapters for vision and speech processing
Core Capabilities
- Multilingual text processing across 23 languages
- Advanced vision capabilities including OCR and chart understanding
- Speech recognition and translation in 8 languages
- Multi-image comparison and video clip summarization
- Function and tool calling capabilities
- 128K token context length for extensive processing
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to process text, vision, and audio inputs in a single neural network, combined with its relatively small size (5.6B parameters) while maintaining competitive performance across multiple benchmarks makes it stand out. It's particularly notable for its strong performance in speech recognition, surpassing specialized models like WhisperV3.
Q: What are the recommended use cases?
The model is ideal for applications requiring memory/compute constrained environments, latency-bound scenarios, strong reasoning (especially math and logic), general image understanding, speech recognition and translation, and multi-modal processing. It's particularly well-suited for commercial and research applications requiring efficient multimodal processing.
