Run Google's Gemma-4 12B model on WSL2 with llama.cpp

A guide details how to run Google's Gemma-4 12B model on Windows Subsystem for Linux 2 (WSL2) using the llama.cpp framework. The process involves updating the WSL environment, installing necessary dependencies like build tools and CUDA if a GPU is available, cloning the llama.cpp repository, and compiling it. Finally, users can run the Gemma-4 model via a command-line interface or a local web server, with instructions provided for downloading the model weights from Hugging Face. AI

IMPACT Enables users to run a specific LLM locally on Windows via WSL2, expanding accessibility for experimentation.

RANK_REASON Guide on using an existing model with a specific framework and environment.

Read on dev.to — LLM tag →

• Gemma-4 12B
• Google
• Hugging Face
• llama.cpp
• WSL2

• product
• infra

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