Recommendations you can check.
by Ollama
Who uses, recommends or left Ollama, in their own words: each a verbatim quote with a link to where it was said.
4 people
I am not affiliated with any of the tools mentioned in this article, but one nice thing about Ollama is that they also optionally support open-weight models hosted in the cloud
A walkthrough of running coding agents against local open-weight models; he names the models and tools he uses.
2026-06-27·magazine.sebastianraschka.com ↗
The easiest way to feel this for yourself is to run one locally tonight: install Ollama or LM Studio, pull a small Qwen model, and talk to an intelligence that lives entirely on your own machine, no cloud required.
Post giving WordPress community members a reading/homework list on AI after a WordCamp keynote
2026-08-20·ma.tt ↗
First and foremost, I use this to talk to local models hosted by Ollama, but secondarily I also use it to interface with other remote services like OpenAI, Anthropic and DeepSeek.
Post describing the AI tools he uses day to day as a techy consumer. This item is Open WebUI, which he uses to talk to Ollama-hosted local models.
2025-01-30·lucumr.pocoo.org ↗
I used ollama before, but when I admitted to this in public half of Twitter told me that I was a noob and llama-server was clearly better and I must have been living in a very deep cave if I did not already know that. I tested their theory.
His write-up of the local-first, privacy-hardened LLM setup he actually runs — hardware, models, agent tooling and sandboxing.
2026-04-02·vitalik.eth.limo ↗
Every entry is a verbatim quote and a link to the public post it came from. Nothing is paraphrased. If it is not on record somewhere public, it is not here.
The verdict is what they actually said: loved and liked are explicit; recommended means they told others to get it; uses means they only say they use it; read is a book on their public shelf with no verdict; mixed and disliked are kept too.
A dashed affiliate link, sponsored or their own label means the post disclosed a relationship. It is shown, never hidden.
The shading behind a date shows how dated a recommendation is for its kind of thing.
The shading behind a date shows how dated a recommendation is, for its kind of thing. Fully green is recent. It drains a quarter at a time as the post gets older, and is empty once it reads as dated.
What counts as old depends on the thing. A laptop praised four years ago has been replaced twice; a book loved twenty years ago is probably still loved. The shading is gone after about:
Stripes mean the post carries no date and the date shown is an estimate. No date at all, no shading.