Ollama: Run Open-Source LLMs Locally with Docker-Like Simplicity

Fri, 01 May 2026 00:00:00 +0000

The world of large language models has evolved at breathtaking speed, but for most users, interacting with these powerful tools still involves sending data to someone else’s servers. Every prompt, every document, every conversation travels over the internet to a cloud API, processed on hardware you do not control, governed by terms of service you probably have not read. For developers, privacy-conscious users, and anyone building AI-powered applications, this architecture creates a fundamental tension: the most capable models require surrendering control of your data.

Ollama emerged as a direct answer to this problem. It is an open-source project that wraps the complexity of running LLMs locally into a command-line interface so simple it feels like using Docker. Pull a model with ollama pull llama3.2, run it with ollama run llama3.2, and you have a fully functional language model running on your own hardware — no cloud connection, no API key, no data leaving your machine. What started as a developer tool has become the de facto standard for local LLM deployment, powering everything from personal AI assistants to enterprise edge deployments.

Twinny: Local LLM Inference for VS Code

Fri, 01 May 2026 00:00:00 +0000

The tension between cloud-dependent AI tools and developer privacy has become one of the defining debates in AI-assisted software development. Services like GitHub Copilot and Cursor offer impressive code completion capabilities, but they require sending your code to external servers. For developers working on proprietary code, in regulated industries, or simply preferring not to share their work product with cloud services, this is a non-starter. The answer is local AI, and Twinny is one of the best ways to access it.

Twinny is a free, open-source VS Code extension that brings local LLM inference directly into your editor. It connects to Ollama – the popular local model runner – and provides AI code completion and chat assistance without any data ever leaving your machine. No subscription, no rate limits, no cloud dependency. Just a local model running on your hardware, integrated into your development workflow.

Local LLM on SoloSoft

Ollama: Run Open-Source LLMs Locally with Docker-Like Simplicity

Twinny: Local LLM Inference for VS Code