~/ / AI articles / Local LLMs on a VPS
Articles on running language models on your own server: the memory you need, installation, settings and what each model can do. Written only from the official documentation of Ollama and the model makers.
Run Open WebUI with Docker and connect it to Ollama on your own server: the commands, the first account, the two connection types and how to update.
Published: Tools you can use: Local LLM Memory Estimator
Constrain a local model's output with a JSON Schema and call Ollama from OpenAI-style clients: what the official docs say, and what is not supported.
Published: Tools you can use: JSON Schema Validator, LLM JSON Repair
Tools, thinking, vision, embeddings: what the labels in the Ollama library mean, which models carry them, and how big the downloads are.
Published: Tools you can use: Local LLM Memory Estimator
Install Ollama on a Linux VPS and keep it running: the install command, the systemd service, environment variables, model storage and updates, from the official docs.
Published: Tools you can use: Local LLM Memory Estimator
Model file plus KV cache: what the Ollama library, the Ollama FAQ and the official model configurations say about the memory a local LLM needs on a VPS.
Published: Tools you can use: Local LLM Memory Estimator
Planning to run Ollama or Dify on a VPS? What the official docs say about memory, CPU-only inference and the ports to keep closed.
Published: Tools you can use: LLM API Cost Calculator