Model Releases
I'm definitely missing something but I don't care, Ollama works great
'Friends don't let friends use Ollama', a blog post so famous it was even published to The Register. Okay, fine, if nothing else I hear llama.cpp has better performance and I don't have to deal with O
"Friends don't let friends use Ollama", a blog post so famous it was even published to The Register. Okay, fine, if nothing else I hear llama.cpp has better performance and I don't have to deal with Ollama's annoying file format, sounds good. Cue me spending all day trying and failing to set up a llama.cpp server, trying three different versions, including the official "llama app". Nothing, I mean nothing I did actually got it to listen on it's server port. No client would connect, not even the official llama-cli. Not even for the official llama app. And when I tried to use llama-cli for local inference, somehow it was slower than Ollama. I was told Ollama was leaving performance on the table, that was the entire reason I even bothered to try setting up llama.cpp. Not for the politics, I don't care about that, I just thought it would run faster on my measly RTX 3060. But no, even that was a lie. I'm sure I'm missing something, but all listening to people did was cost me a day and a few handfuls of hair. This has got to be some kind of prank, why would I go through all of that effort when Ollama works far better than anything else made with llama.cpp? People genuinely expect people to take llama.cpp seriously as an end-user application? I'm a software developer and I couldn't even figure it out. I know llama.cpp isn't really supposed to be it's own server, and instead is meant to build things on top of. Okay, then when is someone going to do that? Why hasn't someone made an Ollama version of llama.cpp (sans early Ollama itself)? This is a joke. This entire experience makes me root for Ollama more. The entire reason I program is because I hate being inconvenienced, so I want to know how computers work so I can make them less inconvenient. llama.cpp is the definition of inconvenient, it doesn't even convene! I even asked an AI to help me and it couldn't! Again, not llama.cpp's fault, just everyone who is delusional enough to think this is a reasonable solution by itself. I'd love to post this on r/LocalLLaMA but I know I'd get downvoted because it only works on their machine and not mine so that makes me a bad person. But another reason I don't want to do that is because "the best way to get an answer online is to post the wrong answer", but I don't want an answer, I genuinely just had to learn the hard way how ridiculous people are who tell you to take llama.cpp seriously as a server. Yes, it's an amazing project, but no, it's not a server, it's a tech demo at best. I'm going to wait for someone to actually make something comparable to Ollama with it, because right now that doesn't exist. I still can't believe I lost an entire day on that garbage. Just for the sake of being "cool". I know this is a shitpost but I'm an old man who needed to rant, lol. I feel scammed. Again, I'm not an old lady, I'm a developer, I've set up plenty of server software in my time, like various databases, this is not new to me. What is new is the server software outright failing to work for no reason at all, no matter how much documentation you pour through or how many different versions you try. I still don't know what the problem was, but either way I don't have a problem if I'm using Ollama. "Friends don't let friends use Ollama", I'm going to compliment that, "Friends don't let friends rip their hair out trying to use the llama.cpp server either". Do not feel uncool for using Ollama, you are saving yourself invaluable time. I'm getting flashbacks to the 2000s/2010s when Linux was the coolest thing ever, then you install it and nothing works and you can't get any work done. But it's so much cooler than Winblows! What a scam. submitted by /u/Illustrious_Car344 [link] [comments]
Related
- Doubled Qwen3.6-27B on a single 3090: ollama 35.7 → llama.cpp+MTP 80.2 tok/s, measured lever by lever
- Honest data: Ollama 6.4 tok/s vs llama.cpp+Vulkan 16 tok/s on Gemma 4 E4B / Radeon 890M iGPU. Setup details inside.
- Been testing Llama.cpp vs Ollama on my Pi 5. The trade-off surprised me.
Source: r/ollama | 2026-10-20