3 ms·

Llama.cpp now has a gui installed by default. It previously lacked this. Times have changed.

by anakaine 6mo ago

OtherShrezzing 6mo ago
While that might be true, for as long as its name is “.cpp”, people are going to think it’s a C++ library and avoid it.
- RobotToaster 6mo ago
  It would make sense to just make the GUI a separate project, they could call it llama.gui.
  - homarp 6mo ago
    it is called llama-barn https://github.com/ggml-org/LlamaBarn https://github.com/ggml-org/LlamaBarn
    - adrian_b 6mo ago
      LlamaBarn is the MacOS app, not the HTTP API server, which is "llama-server". On non-Apple PCs, "llama-server" is what you use, and you can connect to it either with a browser or with an application compatible with the OpenAI API. Perhaps using "llama-server" as the name of the project would have been less confusing for newbies than "llama.cpp". I confess that when I first heard about "llama.cpp" I also thought that it is just a library and that I have to write my own program in order to implement a complete LLM inference backend.
    - mastermage 6mo ago
      this looks nice but is macos only.
  - gettingoverit 6mo ago
    It would make even more sense to rename it to ollama, get a copyright for the name, and see how thieves complain they've been robbed :>
- eterm 6mo ago
  This is the first I'm learning that it isn't just a C++ library. In fact the first line of the wikipedia article is: > llama.cpp is an open source software library
  - deleted 6mo ago
    [deleted]
- figassis 6mo ago
  This is correct, and I avoided it for this reason, did not have the bandwidth to get into any cpp rabbit hole so just used whatever seemed to abstract it away.
- marssaxman 6mo ago
  Wait, it isn't? The name very strongly suggests that it is a text file containing C++ source code; is that not the case?
nikodunk 6mo ago
Having read above article, I just gave llama.cpp a shot. It is as easy as the author says now, though definitely not documented quite as well. My quickstart: brew install llama.cpp llama-server -hf ggml-org/gemma-4-E4B-it-GGUF --port 8000 Go to localhost:8000 for the Web UI. On Linux it accelerates correctly on my AMD GPU, which Ollama failed to do, though of course everyone's mileage seems to vary on this.
- teekert 6mo ago
  Was hoping it was so easy :) But I probably need to look into it some more. llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'gemma4' llama_model_load_from_file_impl: failed to load model Edit: @below, I used `nix-shell -p llama-cpp` so not brew related. Could indeed be an older version indeed! I'll check.
  - roosgit 6mo ago
    I just hit that error a few minutes ago. I build my llama.cpp from source because I use CUDA on Linux. So I made the mistake of trying to run Gemma4 on an older version I had and I got the same error. It’s possible brew installs an older version which doens’t support Gemma4 yet.
    - zozbot234 6mo ago
      And that's exactly why llama.cpp is not usable by casual users. They follow the "move fast and break things" model. With ollama, you just have to make sure you're getting/building the latest version.
      - Eisenstein 6mo ago
        Its not possible to run the latest model architectures without 'moving fast'. The only thing broken here is that they are trying to use an old version with a new model.
mijoharas 6mo ago
Frankly I think the cli UX and documentation is still much better for ollama. It makes a bunch of decisions for you so you don't have to think much to get a model up and running.
zombot 6mo ago
I don't care about the GUI so much. Ollama lets me download, adjust and run a whole bunch of models and they are reasonably fast. Last time I compared it with Llama.cpp, finding out how to download and install models was a pain in Llama.cpp and it was also _much_ slower than Ollama.
- throwa356262 6mo ago
  That is not true. If you today visit a models page on huggingface, the site will show you the exact oneliner you need to run to it on llama.cpp. I didn't measure it, but both download and inference felt faster than ollama. One thing that was definitely better was memory usage, which may be important if you want to run small models on SCB.
- anakaine 6mo ago
  Having picked it up recently and compared to both llama and lm studio - the models I was using ran faster, used less memory, and had a few extra confif options available that the others hadn't implemented yet but were suggested by the model authors. It was easy to install, run, and access the gui to get going.

Llama.cpp now has a gui installed by default. It previously lacked this. Times have changed.

OtherShrezzing 6mo ago

While that might be true, for as long as its name is “.cpp”, people are going to think it’s a C++ library and avoid it.

RobotToaster 6mo ago
It would make sense to just make the GUI a separate project, they could call it llama.gui.
- homarp 6mo ago
  it is called llama-barn https://github.com/ggml-org/LlamaBarn https://github.com/ggml-org/LlamaBarn
  - adrian_b 6mo ago
    LlamaBarn is the MacOS app, not the HTTP API server, which is "llama-server". On non-Apple PCs, "llama-server" is what you use, and you can connect to it either with a browser or with an application compatible with the OpenAI API. Perhaps using "llama-server" as the name of the project would have been less confusing for newbies than "llama.cpp". I confess that when I first heard about "llama.cpp" I also thought that it is just a library and that I have to write my own program in order to implement a complete LLM inference backend.
  - mastermage 6mo ago
    this looks nice but is macos only.
- gettingoverit 6mo ago
  It would make even more sense to rename it to ollama, get a copyright for the name, and see how thieves complain they've been robbed :>
eterm 6mo ago
This is the first I'm learning that it isn't just a C++ library. In fact the first line of the wikipedia article is: > llama.cpp is an open source software library
- deleted 6mo ago
  [deleted]
figassis 6mo ago
This is correct, and I avoided it for this reason, did not have the bandwidth to get into any cpp rabbit hole so just used whatever seemed to abstract it away.
marssaxman 6mo ago
Wait, it isn't? The name very strongly suggests that it is a text file containing C++ source code; is that not the case?

nikodunk 6mo ago

Having read above article, I just gave llama.cpp a shot. It is as easy as the author says now, though definitely not documented quite as well. My quickstart: brew install llama.cpp llama-server -hf ggml-org/gemma-4-E4B-it-GGUF --port 8000 Go to localhost:8000 for the Web UI. On Linux it accelerates correctly on my AMD GPU, which Ollama failed to do, though of course everyone's mileage seems to vary on this.

teekert 6mo ago
Was hoping it was so easy :) But I probably need to look into it some more. llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'gemma4' llama_model_load_from_file_impl: failed to load model Edit: @below, I used `nix-shell -p llama-cpp` so not brew related. Could indeed be an older version indeed! I'll check.
- roosgit 6mo ago
  I just hit that error a few minutes ago. I build my llama.cpp from source because I use CUDA on Linux. So I made the mistake of trying to run Gemma4 on an older version I had and I got the same error. It’s possible brew installs an older version which doens’t support Gemma4 yet.
  - zozbot234 6mo ago
    And that's exactly why llama.cpp is not usable by casual users. They follow the "move fast and break things" model. With ollama, you just have to make sure you're getting/building the latest version.
    - Eisenstein 6mo ago
      Its not possible to run the latest model architectures without 'moving fast'. The only thing broken here is that they are trying to use an old version with a new model.

mijoharas 6mo ago

Frankly I think the cli UX and documentation is still much better for ollama. It makes a bunch of decisions for you so you don't have to think much to get a model up and running.

zombot 6mo ago

I don't care about the GUI so much. Ollama lets me download, adjust and run a whole bunch of models and they are reasonably fast. Last time I compared it with Llama.cpp, finding out how to download and install models was a pain in Llama.cpp and it was also _much_ slower than Ollama.

throwa356262 6mo ago
That is not true. If you today visit a models page on huggingface, the site will show you the exact oneliner you need to run to it on llama.cpp. I didn't measure it, but both download and inference felt faster than ollama. One thing that was definitely better was memory usage, which may be important if you want to run small models on SCB.
anakaine 6mo ago
Having picked it up recently and compared to both llama and lm studio - the models I was using ran faster, used less memory, and had a few extra confif options available that the others hadn't implemented yet but were suggested by the model authors. It was easy to install, run, and access the gui to get going.