Microsoft open-sourced its Phi-4 small language model on Wednesday. The latest artificial intelligence (AI) model in the Phi series was released last month, however, at the time it was only available via the company’s Azure AI Foundry. At the time, the Redmond-based tech giant said that it would soon make the source code of the AI model available in the public domain. Now, interested individuals can access the reasoning-focused AI model via Hugging Face. Microsoft is also letting the model be used for both academic and commercial use cases.
Microsoft Open-Sources Phi-4 AI Model
Shital Shah, a member of the technical staff at Microsoft AI, took to X (formerly known as Twitter) to announce the availability of the Phi-4 AI model’s weights on Hugging Face. The AI model is available with the MIT licence for academic and commercial usage. Interested individuals can access the model listing here.
Launched eight months after the release of the Phi-3 AI model, the SLM is said to offer significant improvements in solving complex reasoning-based queries in areas such as mathematics. The Phi-4 has a context window of 16,000 tokens and was trained on a dataset of 9.8 trillion tokens.
Citing the source of the training data, the Hugging Face listing highlights the dataset comprises publicly available high-quality educational data and code, synthetic data across a wide range of subjects, acquired academic books and Q&A datasets, as well as chat format supervised data.
Notably, it is a text-only model which means it only accepts text as both input and output. The AI model comes with 14 billion parameters. Microsoft states that the AI model was built on a dense decoder-only Transformer architecture.
At the time of release, Microsoft also shared benchmark scores of the AI model. Based on them, the company claimed that the latest iteration of the Phi SLM outperforms the Gemini 1.5 Pro model on the math competition problems benchmark.
The Phi-4 AI model can also be accessed via Microsoft’s Azure AI Foundry. The platform also offers to help developers and enterprises manage AI risks. It also comes with features such as prompt shields, groundedness detection and content filters. These safety capabilities can also be exported to an application using the company’s application programming interface (API).
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