Phi-4

Phi-4-reasoning is a 14-billion parameter transformer-based language model optimized for complex reasoning tasks, including math, coding, algorithmic problem solving, and planning. Trained via supervised fine-tuning of Phi-4 on carefully curated "teachable" prompts and reasoning demonstrations generated using o3-mini, it generates detailed reasoning chains that effectively leverage inference-time compute. Phi-4-reasoning incorporates outcome-based reinforcement learning to produce longer reasoning traces. It outperforms significantly larger open-weight models such as DeepSeek-R1-Distill-Llama-70B and approaches the performance levels of the full DeepSeek-R1 model across a wide range of reasoning tasks. Phi-4-reasoning is designed for environments with constrained computing or latency. Fine-tuned with synthetic data generated by DeepSeek-R1, it provides high-quality, step-by-step problem solving.

Aion-1.0-Instruct is a pre-release small language model introduced in Microsoft Edge as a developer preview for early testing and feedback. It is designed to power Edge’s on-device Prompt and Writing Assistance APIs, giving web developers a faster, smaller, and more efficient model for AI-powered browser experiences. Microsoft previously used Phi-4-mini for these APIs, but its hardware requirements limited availability across devices. Aion-1.0-Instruct expands support to significantly more devices, including machines with less capable GPUs and, through CPU inference, devices without a GPU, while still delivering strong quality for a wide range of web use cases. The model is available in Edge Canary and Dev channels, allowing developers to evaluate it in real-world web scenarios, test API interoperability, and provide feedback before final optimizations. Aion-1.0-Instruct is meant to help developers build AI features directly into websites and browser extensions.