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- What Are Small Language Models (SLMs)? | Microsoft Azure
Small language models (SLMs) are a subset of language models that perform specific tasks using fewer resources than larger models SLMs are built with fewer parameters and simpler neural architectures than large language models (LLMs), allowing for faster training, reduced energy consumption, and deployment on devices with limited resources
- Phi-2: The surprising power of small language models
Phi-2 is now accessible on the Azure model catalog Its compact size and new innovations in model scaling and training data curation make it ideal for exploration around mechanistic interpretability, safety improvements, and fine-tuning experimentation on a variety of tasks
- Tiny but mighty: The Phi-3 small language models with big potential
The company announced today the Phi-3 family of open models, the most capable and cost-effective small language models available Phi-3 models outperform models of the same size and next size up across a variety of benchmarks that evaluate language, coding and math capabilities, thanks to training innovations developed by Microsoft researchers
- Phi Open Models - Small Language Models | Microsoft Azure
Explore Phi models, efficient small language models (SLMs) for generative AI applications Learn more about Phi in Azure AI Foundry
- Orca 2: Teaching Small Language Models How to Reason
At Microsoft, we’re expanding AI capabilities by training small language models to achieve the kind of enhanced reasoning and comprehension typically found only in much larger models
- Understanding Small Language Modes | Microsoft Community Hub
Small Language Models (SLMs) bring AI from the cloud to your device Unlike Large Language Models that require massive compute and energy, SLMs run locally,
- Understanding Small Language Modes | Microsoft Community Hub
Performance Benchmarks Small Language Models are built for speed and efficiency On modern NPUs like the Snapdragon X Elite, 1–2 billion parameter models such as Phi-3-mini can achieve sub-80 millisecond inference latency for short prompts nearly 10× faster than running the same task via a cloud API
- Introducing Phi-3: Redefining what’s possible with SLMs
Groundbreaking performance at a small size Phi-3 models significantly outperform language models of the same and larger sizes on key benchmarks (see benchmark numbers below, higher is better) Phi-3-mini does better than models twice its size, and Phi-3-small and Phi-3-medium outperform much larger models, including GPT-3 5T All reported numbers are produced with the same pipeline to ensure
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