41–50 of 60 posts
- stop using ollama - https://sleepingrobots.com/dreams/stop-using-ollama/
How did they raise that amount of money if they are so hated, I see only bad comments everywhere about ollama. Not a fan of them myself, but they played a good part in local ai since the beginning. The investors screw everything: Ollama announced an $88 million financing on July 9, 2026. The named participants were: Investment firms and organizations Benchmark — represented by Peter Fenton Theory Ventures — Tomasz Tu…
Why blame the investors? You went out of your way to even name them so we can bash them, why? Ollama founders sought them. Ollama founders wanted the money. Ollama founders took the money. Ollama founders took all the decisions that made people now dislike Ollama. Nobody forced their hands, it was their plan all along...
I get that people here have reasons to hate on Ollama but it has two genuinely strong points: - it makes it very easy to use open models with a lot of harnesses and assistants via `ollama launch`; Their $20 subscription is very generous, and they claim not to log or train on your data. I will be curious to see if their subscription ever supports the ~3T open weights models announced this week.
> $20 subscription is very generous, and they claim not to log or train on your data. The principle of running locally is that you’re not in the cloud.
Earlier quoted context omitted.
Taking credit for other people's work while raising millions? Yeah, pretty bad and relevant.
See also: why friends don't let friends use permissive software licenses. The llama.cpp authorized ollama to do this... Unintentionally.
>The project’s binary distributions didn’t include the required MIT license notice for the llama.cpp code they were shipping. This isn’t a matter of open-source etiquette, the MIT license has exactly one major requirement: include the copyright notice. Ollama didn’t.
Earlier quoted context omitted.
I don't use local models often enough, but this convinced me to uninstall ollama. Now I need to figure out which of the options at the end of that post is the best alternative for me.
llama.cpp? Ollama is/was based on that.
For those new to llama.cpp, the llama-server component running in "router mode" is fantastic; you place your common configuration in a defaults section of an ini file, and then model specific configuration in separate sections of the ini file. You can switch between models, on the fly, using the API, and the built-in web front-end for llama-server supports model switching as a drop down menu. Llama-server can just always be running, in the background (you can set an idle time for it to automatically unload weights to free vram/ram, and a maximum simultaneously running model count which will evict models on an LRU basis before loading new ones, if the count is exceeded).
llama-bench is another great tool included in llama.cpp, where you can provide ranges of options to test, and just let it run through all the variations that you requested, then take the best performing and add those settings to the ini file above.
There are a lot of optional tunables that can really improve performance with llama-server. E.g., typical average tok/sec generation speed improved over 7X for Gemma4 31B, on my laptop, with tuned batch-size / ubatch-size and enabling both spec-type draft-mtp and ngram-mod (with some custom settings on both). I.e., even though you don't need to do this for llama-server to be useful, it can be worth your while to spend a little time optimizing settings for your favorite models especially if your hardware is marginal.
- stop using ollama - https://sleepingrobots.com/dreams/stop-using-ollama/
This is all lovely and I wish them the best. But please don't use ollama, or their quants. Not only is the app itself slower than pure llamacpp. But their quants are often no where near the best. I really hope people start with something like unsloth, as their software and quants are really much better all around.
For anyone who may not be aware it exists: https://unsloth.ai/docs/new/studio
- stop using ollama - https://sleepingrobots.com/dreams/stop-using-ollama/
Will Ollama finally properly credit llama.cpp ? Or will they continue to rebrand new llama.cpp features as their own?