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# Microsoft’s Phi-4 AI Model Goes Open Source!
- URL: https://itsfoss.com/news/microsofts-phi-4-ai-model-open-source/
- Published: 2025-01-09T10:27:18.000Z
- Updated: 2025-01-09T10:27:18.000Z
- Description: Microsoft's Phi-4 AI model, one of Azure's exclusive options, is now available for everyone to test!
- Author: Sourav Rudra
- Tags: AI Spotlight, News, #Import 2025-11-08 21:15

The rise of open source AI models has been a game changer, with many organizations and individuals opting for these models over proprietary ones due to their lower entry costs.

These models also enable fine-tuning for specific use cases, offering unmatched flexibility and fostering collaboration across industries.

[Microsoft](https://www.microsoft.com/?ref=itsfoss.com) has been a notable player in the space, and following [an announcement](https://x.com/sytelus/status/1877015492126220594?ref=itsfoss.com) by Shital Shah, an engineer at their research division, they have open-sourced Phi-4, a small language model ([*SLM*](https://www.ibm.com/think/topics/small-language-models?ref=itsfoss.com)).

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## Phi-4 Goes Open: What To Expect?

![a screenshot of the phi-4 page on hugging face](https://itsfoss.com/content/images/2025/01/Phi-4_HuggingFace_Page.png)

Phi-4 on Hugging Face.

Distributed under the [MIT License](https://opensource.org/license/mit?ref=itsfoss.com), Phi-4 is **a state-of-the-art 14 billion parameter SML** that has been tailored for carrying complex reasoning tasks, outperforming popular models like [Llama 3.3](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3%5F3/?ref=itsfoss.com) and [GPT-4o mini](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/?ref=itsfoss.com) in benchmarks like [MATH](https://arxiv.org/abs/2103.03874?ref=itsfoss.com) and [GPQA](https://arxiv.org/abs/2311.12022?ref=itsfoss.com).

Initially exclusive to [Azure AI Foundry](https://ai.azure.com/?ref=itsfoss.com), Phi-4 is now available to everyone, offering **a powerful utility for tasks requiring complex reasoning and nuanced understanding**. It can be applied in areas like natural language inference, text summarization, content generation, and more.

This flexibility makes Phi-4 suitable for a wide range of applications, including research, product development, and experimentation in AI-powered solutions.

**As for the benchmarks**, here is a table that shows the Phi-4 pitched against other popular models, both small and large. 👇

![a screenshot that shows a bunch of tables with benchmark numbers pitching the phi-4 model against other models](https://itsfoss.com/content/images/2025/01/Phi-4_Benchmarks.png)

Source: Microsoft Research

If you're looking for a more detailed understanding of Phi-4, be sure to check out the [technical paper](https://arxiv.org/pdf/2412.08905?ref=itsfoss.com) for an in-depth summary. It provides valuable insights into how the model works and the research behind it.

### Want To Check It Out?

The downloadable weights for Phi-4 can be found on [Hugging Face](https://huggingface.co/microsoft/phi-4?ref=itsfoss.com), where you will also find the model card. If you are still eager to learn more, then you can go through the initial [announcement blog](https://techcommunity.microsoft.com/blog/aiplatformblog/introducing-phi-4-microsoft%E2%80%99s-newest-small-language-model-specializing-in-comple/4357090?ref=itsfoss.com).

[Phi-4 (Hugging Face)](https://huggingface.co/microsoft/phi-4?ref=itsfoss.com)

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