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Qwen 2.5 Coder 7B is the most accurate of the three for Python and TypeScript completions. Phi-4 Mini (3.8B) uses the least VRAM and runs nearly twice as fast. Pick it when memory or latency counts more than raw accuracy. Gemma 3 4B sits in the middle. It is the best choice when you need one model for code, commit messages, docs, and error explanations. Below are the benchmark numbers, the test method, and how to set up each model in VS Code or Neovim.

Small Language Models, sub-4B parameter models built to run on local hardware, now handle most of the edge AI work that used to need the cloud. Phi-4 , Gemma 3 , and Llama 3.2-1B run offline on Raspberry Pi boards, phones, and industrial PLCs. The economics, latency, and privacy story all point the same way: edge first.

What Counts as a Small Language Model

In 2023, “small” meant under 13B parameters. Today, three tiers matter for edge work.