To any ollama.com dudes and dudettes reading this: why won't you offer any embedding models on your subscription when they are readily supported by the software and fairly efficient to run?
Or, you know. Don't tell me what to do. One dirty hand washes another and many of llama.cpp's new features are straight copies of ollama functionality. You do you of course. But stop denying them their contribution to this ecosystem and stop denying me my agency to salve your politics.
This article is really helpful for finding alternatives. I was already using LMStudio but I love that I now know about a couple of true open source alternatives I can try out.
A year and still no implementation for such a basic need as offloading MoE layers onto the CPU selectively. On llama.cpp I can get models like Qwen 35BA3B running partially on gpu/cpu with 40t/s on a laptop thanks to --n-cpu-moe but on this VC funded joke it would be simply unusable.
I can't quite understand how you make a wrapper so much worse than the code you're ripping out.
>This funding is fuel for what’s ahead. Ollama sits front and center in the open model ecosystem
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 Tunguz
8VC — Alex Kolicich
Y Combinator
Garage Capital
Pace Capital
49 Palms
GTMFund
Individual investors
Solomon Hykes — Docker founder
Aaron Katz — ClickHouse CEO
Spencer Kimball — Cockroach Labs co-founder and GIMP co-creator
Quinn Slack — Amp CEO
Marianna Tessel — Cisco board member
Michael Montano — former Twitter head of engineering
Other unnamed angel investors
>like lmstudio and google/alphabet maybe!
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.
I think the "8.9 million developers use ollama" figure they throw around is contrived. I found this 2025 article which posits that there were 47.2 million software developers in the world. Even the number of developers has doubled in a year (plausible if you account for the rise in vibe coding), I think it's very unlikely that 1 in 10 developers use ollama.
No no no…. You see, with AI, everyone and their dog is a developer now. 8.9 million looks pretty pathetic when considering the global computer-using population.
A lot of hate for Ollama in this thread. Am I understanding correctly that it is all based on not crediting llama.cpp correctly? I can't find any other argument against it, other than some minor performance differences. Where Ollama stands out is user interface. It's easy to overlook how difficult and important that is.
I dumped ollama yesterday after reading a similar thread. I definitely don’t condone what ollama has done but yes, definitely their UX is far better - as an end user.
Their docker-like extending and defining new models is really simple (coming from a docker background).
Installing new models with llama.cpp seems nontrivial. Perhaps it was using the mac dmg instead of curl-pipe-sh.
Unfortunately then llama.cpp crashed my laptop - no error, no feedback, just frozen desktop and reboot.
Went back to a much slower experience with ollama but it just works out of the box… sorry to say.
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[ 3.5 ms ] story [ 22.2 ms ] threadNote to self, Enshittification ahead. Don't use any ollama services unless it's calling an industry standard api.
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.
- https://sleepingrobots.com/dreams/stop-using-ollama/
A year and still no implementation for such a basic need as offloading MoE layers onto the CPU selectively. On llama.cpp I can get models like Qwen 35BA3B running partially on gpu/cpu with 40t/s on a laptop thanks to --n-cpu-moe but on this VC funded joke it would be simply unusable. I can't quite understand how you make a wrapper so much worse than the code you're ripping out.
>This funding is fuel for what’s ahead. Ollama sits front and center in the open model ecosystem
No.
Then put those LLMs to work and build an open source alternative to everything that Ollama is doing.
After all, open source is a pricing weapon to race everything to $0.
Georgi Gerganov, the author of llama.cpp, is the real hero here.
https://llama.app/
Were they so enraptured with the “docker for LLMs” line?
Investment firms and organizations
Benchmark — represented by Peter Fenton Theory Ventures — Tomasz Tunguz 8VC — Alex Kolicich Y Combinator Garage Capital Pace Capital 49 Palms GTMFund
Individual investors
Solomon Hykes — Docker founder Aaron Katz — ClickHouse CEO Spencer Kimball — Cockroach Labs co-founder and GIMP co-creator Quinn Slack — Amp CEO Marianna Tessel — Cisco board member Michael Montano — former Twitter head of engineering Other unnamed angel investors >like lmstudio and google/alphabet maybe!
Investors are not free
I will be curious to see if their subscription ever supports the ~3T open weights models announced this week.
https://www.slashdata.co/post/global-developer-population-tr...
Their docker-like extending and defining new models is really simple (coming from a docker background).
Installing new models with llama.cpp seems nontrivial. Perhaps it was using the mac dmg instead of curl-pipe-sh.
Unfortunately then llama.cpp crashed my laptop - no error, no feedback, just frozen desktop and reboot.
Went back to a much slower experience with ollama but it just works out of the box… sorry to say.