Advanced Small Language Model for Complex Reasoning Tasks
Phi-4, developed by Microsoft, is an advanced small-scale language model optimized for high performance in reasoning, mathematics, and coding tasks. Trained on enhanced datasets with synthetic math and coding data, Phi-4 delivers superior efficiency, making it ideal for resource-limited environments and versatile enough for multimodal applications.
Phi-4 is Microsoft's latest small language model, designed for computational efficiency without sacrificing performance, especially in complex reasoning tasks such as mathematics and coding.
The model utilizes specialized synthetic training datasets, significantly enhancing its abilities in coding, mathematics, and logical inference, outperforming many larger models.
Phi-4 introduces advanced multimodal variants like Phi-4-Multimodal, which combine language, visual, and speech processing, enabling broader and richer AI interactions.
Available in multiple efficient configurations, such as the Phi-4-Mini (3.8 billion parameters) and Phi-4-Multimodal (5.6 billion parameters), these variants offer powerful performance suitable for diverse computational settings.
Phi-4 demonstrates exceptional benchmark performance, including HumanEval (coding), GSM8K (mathematics), and multimodal evaluations, indicating its versatility across varied AI tasks.
Phi-4 is accessible through platforms like Hugging Face and Azure AI Foundry, fostering collaboration and innovation within the global AI research and developer community.