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In this video, I'll be telling you about Microsoft Phi-4 which is a new Opensource LLM that is very small and only 14 billion parameters but beats GPT-4O, Qwen-2.5 and Much more! Today, We'll be testing it and we'll see how well it performs.

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Key Takeaways:

🎯 Microsoft's Phi-4 Model is a small language model with 14 billion parameters, offering high-quality results for tasks like coding, reasoning, and math.

🚀 Beats Larger Models: Phi-4 outperforms Qwen 2.5 14B and even challenges Llama 3.3 70B and GPT-4O in benchmarks like GPQA and math.

💻 Run Locally: You can run Phi-4 easily on Mac (24GB RAM) or a system with 16GB VRAM, making it super accessible for developers and AI enthusiasts.

📊 Amazing Benchmarks: This model scores exceptionally well in complex reasoning, coding, and synthetic data tasks while maintaining efficiency.

🛠️ Available on HuggingFace & Ollama: Download and run Phi-4 locally for free or test it via Azure AI Foundry. Perfect for quick deployment!

📈 Efficient Inference: With its small size, Phi-4 ensures cheaper inference costs and works seamlessly with tools like OpenWebUI or API setups.

📜 Powerful Pre-Training: Based on synthetic data and GPT-4O insights, Microsoft has set a new standard for small AI models with Phi-4.

🔔 Perfect for Coders: Whether it’s HTML, Python scripts, or advanced AI tasks, Phi-4 delivers outstanding performance that rivals even bigger models.

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Timestamps:

00:00 - Introduction
01:01 - NinjaChat (Sponsor)
02:09 - About Phi-4 & Local Weights
04:50 - Testing
10:33 - Final Results, Charts & Thoughts
12:39 - Ending

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