I assumed from the name that it only ran llama-derived models, rather than whatever is available at huggingface. Is that not the case?
No, they have quite a broad list of models: https://ollama.com/search [edit] Oh and apparently you can also directly run some models directly from HuggingFace: https://huggingface.co/docs/hub/ollama
Just use llama.cpp. Ollama tried to force their custom API (not the openai standard), they obscure the downloaded models making them a pain to use with other implementations, blatantly used llama.cpp as a thin wrapper without communicating it properly and now has to differentiate somehow to start making money.
If you've ever used a terminal, use llama.cpp. You can also directly run models from llama.cpp afaik.
Huge caveat: For the $20/mo subscription Google hasn't made clear if they train on your data. Anthropic and OAI on the other hand either clearly state they don't train on paid usage or offer very straightforward opt-outs. https://geminicli.com/docs/faq/ > What is the privacy policy for using Gemini Code Assist or Gemini CLI if I’ve subscribed to Google AI Pro or Ultra? > To learn more about your privacy policy and te…
I have no idea at all whether the GCP "Service Specific Terms" [1] apply to Gemini CLI, but they do apply to Gemini used via Github Copilot [2] (the $10/mo plan is good value for money and definitely doesn't use your data for training), and states: Service Terms 17. Training Restriction. Google will not use Customer Data to train or fine-tune any AI/ML models without Customer's prior permission or instruction. [1] ht…
Yeah Github of course has proper enterprise agreements with all the models they offer and they include a no-training clause. The $10/mo plan is probably the best value for money out there currently along with Codex $20/mo (if you can live with GPT's speed).
Huge caveat: For the $20/mo subscription Google hasn't made clear if they train on your data. Anthropic and OAI on the other hand either clearly state they don't train on paid usage or offer very straightforward opt-outs. https://geminicli.com/docs/faq/ > What is the privacy policy for using Gemini Code Assist or Gemini CLI if I’ve subscribed to Google AI Pro or Ultra? > To learn more about your privacy policy and te…
Are you sure about OpenAI? I thought they actually do retain your agent chats (training I am less concerned about personally). Anthropic has an option to opt out of training and delete the chats from their cloud in 30 days.
I was only talking about training so you're probably right about retention - I care more about training.
> I realized I looked at this more from the angle of a hobbiest paying for these coding tools. Someone doing little side projects—not someone in a production setting. I did this because I see a lot of people signing up for $100/mo or $200/mo coding subscriptions for personal projects when they likely don’t need to. Are people really doing that? If that's you, know that you can get a LONG way on the $20/month plans fr…
I use local models + openrouter free ones. My monthly spend on ai models is I'm not cheap, just ahead of the curve. With the collapse in inference cost, everything will be this eventually I'll basically do $ man tool | or even $ cat source | Things I used to do intensively I now do lazily. I've even made a IEITYuan/Yuan-embedding-2.0-en database of my manpages with chroma and then I can just ask my local documentatio…
> I'm not cheap, just ahead of the curve.
I'm not convinced.
I'm convinced you don't value your time. As Simon said, throw $20-$100/mo and get the best state of the art models with "near 0" setup and move on.
My experience: even for the run of the mill stuff, local models are often insufficient, and where they would be sufficient, there is a lack of viable software. For example, simple tasks CAN be handled by Devstral 24B or Qwen3 30B A3B, but often they fail at tool use (especially quantized versions) and you often find yourself wanting something bigger, where the speed falls a bunch. Even something like zAI GLM 4.6 (thr…
Have you tried llama.vscode [0]? I use the vim equivalent, llama.vim [1] with Qwen3 Coder 30B and personally feel that it's better than Copilot. I have hot keys that allow me to quickly switch between the two and find myself always going back to local.
Nah - given the ergonomics + economics, local coding models are not atm that viable. I like all things local even if just for safety of keeping healthy competitive ecosystem. And I can imagine really specialised uses cases where I run an 8B not-so-smart model to process oodles of data on my local 7900xtx or similar. Got older m2 mbp with 96gb (v)ram and try all things local that fit. Usually LMStudio for the speed add in MLX format models on ASI (as end point; plus chat for vibes test; LMStudio omission from the OP blog post makes me question the post), or llama.cpp for GGUF (llama.cpp is the OG; excellent and universal engine and format; recently got even better). Looking at how agents work - an agent smarts of Claude Code or Codex in using the tools feels like it's half its success (the other half the underlying LLM smarts). From the training on baked in 'Tool Use & Interleaved Thinking' on the right tools in a right way, to the trivial 'DONOTDO bad idea to fill your 100K useful context with random content of multi-MB file as prompt'. The $20/mo plans are insanely competitive. OpenaI is generous with Codex, and in addition to terminal that I mostly use, there is the VSCode addon as well as use in Cline or Roo. Cursor offers in-house model fast and good, insane economy reading large codebases, as well BYOK to latest-greatest LLMs afaik. Claude Code $20/mo is stingy with quotas, but can be supplement with Z.ai standing in - glm-4.7 as of yesterday (saw no difference glm-4.6 v.v. sonnet-4.5 already v.good). It's a 3 lines change to ~/.claude/settings.json to flip Z.ai-Anthropic back and forth at will (e.g. when paused on one to switch to the other). Have not tried the Cerebras high tok/s but wd love to - not waiting makes a ton of difference to productivity.
I have no idea at all whether the GCP "Service Specific Terms" [1] apply to Gemini CLI, but they do apply to Gemini used via Github Copilot [2] (the $10/mo plan is good value for money and definitely doesn't use your data for training), and states: Service Terms 17. Training Restriction. Google will not use Customer Data to train or fine-tune any AI/ML models without Customer's prior permission or instruction. [1] ht…
Thanks for those links. GitHub Copilot looks like a good deal at $10/mo for a range of models. I originally thought they only supported the previous generation models i.e. Claude Opus 4.1 and Gemini 2.5 Pro based on the copy on their pricing page [1] but clicking through [2] shows that they support far more models. [1] https://github.com/features/copilot#pricing [2] https://github.com/features/copilot/plans#compare
Yes, it's a great deal especially because you get access to such a wide range of models, including some free ones, and they only rate limit for a couple minutes at a time, not 5 hours. And if you go over the monthly limit you can just buy more at $0.04 a request instead of needing to switch to a higher plan. The big downside is the 128k context windows.
Lately Copilot have been getting access to new frontier models the same day they release elsewhere. That wasn't the case months ago (GPT 5.1). But annoyingly you have to explicitly enable each new model.