mljourney

Once you have Ollama running and a few models downloaded, you’ll spend a surprising amount of time managing those models — pulling new ones, removing ones you no longer use, checking what’s loaded, switching between versions. The Ollama CLI has a clean set of commands for all of this, and knowing them well saves you … Read more

Whether you’re troubleshooting a broken install, switching to a different setup, or just freeing up disk space, uninstalling Ollama is slightly more involved than most applications. The binary and the service are one thing — the model files (which can be tens or hundreds of gigabytes) are stored separately and don’t get removed by a … Read more

Running Ollama behind a reverse proxy gives you things the raw API doesn’t: a clean domain name instead of an IP and port, HTTPS so connections are encrypted, basic authentication to keep your models private, and the ability to put Ollama on a standard port (80/443) that doesn’t need special firewall rules. If you’re running … Read more

Ollama’s behaviour is almost entirely configurable through environment variables — where it stores models, what address and port it listens on, how long it keeps models in memory, how many parallel requests it handles. The defaults are sensible for a single-user local setup, but as soon as you want to customise anything — move models … Read more

You’ve installed Ollama, you try to run a model, and nothing happens — or you get a cryptic error you’ve never seen before. This is frustrating, but nearly every Ollama startup issue falls into one of a handful of root causes. This guide works through them systematically, from the most common to the more obscure, … Read more

Gemma 3 is Google’s best open-weight model family to date, and it’s a significant step up from Gemma 2. The standout version is the 27B model, which competes with much larger open-source models on reasoning and instruction following. But the whole family is worth knowing — from the 1B model that runs on almost anything … Read more

By default, Ollama only listens on localhost — it accepts connections from your own machine and ignores everything else. That’s fine for solo use, but if you want to query Ollama from another device on your network, run Open WebUI on a different machine, access it from a phone or tablet, or share it with … Read more

Ollama on Windows runs on CPU by default, but if you have an NVIDIA GPU, you’re leaving a lot of performance on the table. With CUDA enabled, a 7B model that generates 4–6 tokens per second on CPU can hit 50–80 tokens per second on a mid-range GPU — the difference between something that feels … Read more

Mistral Small 3 is one of the most interesting models to land in the local LLM space in 2025. At 24 billion parameters, it sits in an underserved spot — larger than the 7B class where most consumer hardware plays, but far more accessible than 70B models that require server-grade RAM. What makes it notable … Read more

WSL2 (Windows Subsystem for Linux 2) gives you a full Linux kernel running inside Windows — and Ollama on WSL2 is a genuinely good setup. You get native Linux performance, GPU passthrough for NVIDIA cards, and the ability to run Ollama alongside your Linux development toolchain without leaving Windows. If you’re a developer who primarily … Read more