Llama.cpp vs. Ollama: Which is the Best Way to Run LLMs Offline? The era of "local AI" is officially here. With the release of powerful models like Llama 3, Mistral, and Phi-3, many developers and enthusiasts are looking to run Large Language Models (LLMs) on their own hardware. Why go offline? The reasons are simple: Privacy, zero latency from the cloud, no per-token costs, and the ability to experiment without restrictions. But once you decide to go local, you face the first big hurdle: How do you actually run these models? The two heavyweights in the scene are llama.cpp and Ollama . While they are related, they serve very different needs. In this post, we’ll break down the differences to help you decide which is right for your workflow. The Contenders: A Quick Overview Before diving into the comparison, let’s define what these tools actually are: llama.cpp: A high-performance C++ implementation of the Llama architecture (and many others). It is the "engine" tha...
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Showing posts from August, 2026