You’ve got 100 GB of PDFs, notes, and exported chat logs you’d love to query with natural language. So you reach for the standard RAG playbook: chunk everything, embed it, store the vectors in FAISS or a hosted vector DB. Then you check the index size and it’s 150–700 GB — larger than the data […]
Read More →Running LLMs locally has become a normal part of how developers work. Two tools dominate this space: llama.cpp and Ollama. They look like competitors, but the relationship is more direct — Ollama is built on top of llama.cpp. This post covers the technical differences, where each performs better, and when to use one versus the other. Table of […]
Read More →Privacy is becoming a luxury in the AI world. If you’re tired of sending your data to the cloud every time you ask a question, running a model locally is the answer. Today, we’re looking at Qwen 3.5 9B—a powerhouse model from Alibaba—and how to get it running on your own machine using Ollama. Whether you’re a […]
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