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You're paying per message for Claude or ChatGPT — and for a lot of what you do, that's the right call. But not everything needs a frontier model: formatting a spreadsheet, summarizing a doc, running a background automation at 2am. That's the gap a tool called Ollama fills, and it's worth understanding because "AI you can run for free" is not the same claim as "AI you should always use instead."
What it actually is: Ollama is a free, open-source way to run AI language models — on your own computer, or now on Ollama's own cloud servers ("Ollama Cloud"). It isn't an AI itself — it's the player, not the movie. The actual models (Llama, Qwen, DeepSeek, Gemma, Hermes, and dozens more) are built by other labs and released "open weight," so anyone can download and run them instead of only reaching them through one company's paid API. It plugs directly into tools you probably already use — Claude Code, Codex, OpenCode, VS Code, n8n — so pointing one at Ollama instead of a frontier provider doesn't change your workflow, just which model does the work.
What it's not: not a chatbot brand (no personality, it's infrastructure); not automatically private in the cloud tier (your prompts go to Ollama's servers — they say they don't train on your data, but that's a policy promise, not a local guarantee); not as strong as Claude or GPT-5-class models on the hardest reasoning or coding; and not free at scale in the cloud — Ollama Cloud runs $20–$100/month, still far cheaper than frontier pricing, but a real bill.
How it compares: OpenRouter is a marketplace — one account, 500+ models (open and closed) across 80+ providers, pass-through pricing, no markup. Ollama is different: it's the tool that runs open models directly, either on your machine (free, fully private, offline-capable) or now on Ollama's own hardware (no GPU needed, still cheaper than frontier APIs).
A few real models worth knowing: Llama 3.1 (Meta, still the most-downloaded model on Ollama by a wide margin), Qwen 3.6 (Alibaba, strong general coding model), GLM 5.1 (Z.AI, formerly Zhipu, built for agents), DeepSeek V4 Pro (strong reasoning per dollar), and Hermes 4.3 (Nous Research — deliberately built without heavy built-in guardrails, which cuts both ways).
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Where this actually gets used: budget coding (route boilerplate to an open model, save Claude for the hard problems), privacy-sensitive work (fully local, nothing leaves the machine), always-on automation (a metered bill adds up fast — this is also where dedicated agent apps like Hermes Agent and OpenClaw come in, both built to run on an open model instead of a paid one), offline work, and just experimenting for free.
The honest tradeoff: local needs decent hardware, cloud is still a subscription (to a server, just not a frontier AI company's), and open models still generally trail the best closed ones on the hardest work. It's one more decision to manage — but for the routine stuff, that decision pays for itself.
The full breakdown — including how Hermes (the model) differs from Hermes Agent (the assistant), and a free copy-paste prompt to figure out which of your own tasks could actually move — is on the site.
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— Jerry