Description
Phi-4-Reasoning-Vision-15B is a compact open-weight multimodal reasoning model developed by Microsoft, built on the Phi-4-Reasoning language model backbone and the SigLIP-2 vision encoder. This model utilizes a mid-fusion architecture, where the vision encoder converts images into visual tokens, which are then projected into the language model's embedding space. This innovative approach combines the strengths of both pretrained components while maintaining manageable training and inference costs.
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The model is capable of processing text and images, with a context length of 16,384 tokens. It has been trained using Supervised Fine-Tuning (SFT) on a carefully curated dataset that includes both reasoning and non-reasoning data. This allows Phi-4-Reasoning-Vision-15B to perform extended chain-of-thought reasoning for complex tasks, such as mathematical and scientific reasoning, while also handling direct inference for perception-focused tasks like captioning and object detection.
Phi-4-Reasoning-Vision-15B is particularly effective in memory- or compute-constrained environments, making it ideal for general-purpose multimodal AI systems. Its primary use cases include scientific and mathematical reasoning over visual inputs, as well as computer-use agent tasks that involve interpreting screen content and localizing GUI elements. The model is also capable of general multimodal tasks such as image captioning, visual question answering, and optical character recognition.
The model's training involved 240 NVIDIA B200 GPUs over a period of four days, with a focus on safety and alignment. It incorporates a safety post-training approach that includes a mixture of open-source and in-house generated synthetic datasets to ensure appropriate behavior in response to harmful content. Developers are advised to consider the model's limitations, particularly in high-risk scenarios, and to apply responsible AI practices when integrating it into applications.
- CategoryAI Models & LLMs
- Pricing ModelOpen source
- DeploymentCloud
- PlatformsWeb
Phi-4-reasoning-vision-15B Highlights
Model Type: Multimodal
API Available: Yes
License: MIT
Parameters: 15B
Context Length: 16,384 tokens
Training GPUs: 240
Training Time: 4 days
Fine-tuning Support: Yes
Multimodal: Yes
Getting Started with Phi-4-reasoning-vision-15B
Access model: Visit the Hugging Face page for Phi-4-Reasoning-Vision-15B.
Authenticate: Set up your Hugging Face account for API access.
Set up environment: Ensure your system meets the technical requirements.
Integrate via API: Use the provided API documentation to integrate the model into your application.
Optimize: Fine-tune the model based on your specific use case.
Phi-4-reasoning-vision-15B's Use Cases
- Scientific Reasoning
- Computer-Use Agent Tasks
- Image Captioning
- Visual Question Answering
- Optical Character Recognition
