Microsoft Phi
Small language model family (Phi-3/4 lineage) emphasizing strong quality per parameter; weights on Hugging Face under Microsoft licenses per release.
Why it is included
Reference for efficient SLMs on device and in Azure—popular in education and edge demos.
Best for
Low-latency assistants where small checkpoints matter.
Strengths
- Small size
- Good benchmarks for scale
- ONNX story
Limitations
- Not all releases equally open; terms vary
Good alternatives
TinyLlama · SmolLM · Gemma
Related tools
AI & Machine Learning
Google Gemma
Google’s smaller open **weights** Gemma line (Gemma 2/3, etc.) with Gemma license terms, plus `gemma.cpp` for lightweight CPU inference.
AI & Machine Learning
TinyLlama
1.1B-parameter Llama-architecture model trained on ~3T tokens—Apache-2.0 weights for fast experiments and teaching.
AI & Machine Learning
SmolLM
Hugging Face TB small LM family (135M–1.7B) with Apache-2.0 weights aimed at on-device and edge quality per size.
AI & Machine Learning
MLC LLM
Universal deployment stack compiling models to Vulkan, Metal, CUDA, and WebGPU via TVM/Unity for phones, browsers, and servers.
AI & Machine Learning
MNN
Alibaba’s lightweight inference engine for mobile and edge—used for on-device LLMs and classic CV models with aggressive optimization.
AI & Machine Learning
Ollama
Local LLM runner and model library with simple CLI and API for workstation inference.