31–40 of 222 posts
Earlier quoted context omitted.
you can pull directly from huggingface with llama.cpp, and it also has a decent web chat included
Does it have a model registry with an API and hot swapping or you still have to use sometime like llama swap as suggested in the article ? Or is it CLI?
https://github.com/ggml-org/llama.cpp/blob/master/tools/serv...
The progression follows the pattern cleanly:
1. Launch on open source, build on llama.cpp, gain community trust
2. Minimize attribution, make the product look self-sufficient to investors
3. Create lock-in, proprietary model registry format, hashed filenames that don’t work with other tools
4. Launch closed-source components, the GUI app
5. Add cloud services, the monetization vectorFor most users that wanted to run LLM locally, ollama solved the UX problem. One command, and you are running the models even with the rocm drivers without knowing. If llama provides such UX, they failed terrible at communicating that. Starting with the name. Llama.cpp: that's a cpp library! Ollama is the wrapper. That's the mental model. I don't want to build my own program! I just want to have fun :-P
For most users that wanted to run LLM locally, ollama solved the UX problem. One command, and you are running the models even with the rocm drivers without knowing. If llama provides such UX, they failed terrible at communicating that. Starting with the name. Llama.cpp: that's a cpp library! Ollama is the wrapper. That's the mental model. I don't want to build my own program! I just want to have fun :-P
Llama.cpp now has a gui installed by default. It previously lacked this. Times have changed.
No mention of the fact that Ollama is about 1000x easier to use. Llama.cpp is a great project, but it's also one of the least user friendly pieces of software I've used. I don't think anyone in the project cares about normal users. I started with Ollama, and it was great. But I moved to llama.cpp to have more up-to-date fixes. I still use Ollama to pull and list my models because it's so easy. I then built my own set…
Exactly. The blog post states that the alternatives listed are similarly intuitive. They are not. If you just need a chat app, then sure, there’s plenty of options. But if you want an OpenAI compatible API with model management, accessibility breaks down fast. I’m open to suggestions, but the alternatives outlined in the blog post ain’t it.
> LM Studio gives you a GUI if that’s what you want. It uses llama.cpp under the hood, exposes all the knobs, and supports any GGUF model without lock-in.
> Jan(https://www.jan.ai/) is another open-source desktop app with a clean chat interface and local-first design.
> Msty(https://msty.ai/) offers a polished GUI with multi-model support and built-in RAG. koboldcpp is another option with a web UI and extensive configuration options.
API wise: LM Studio has REST, OpenAI and more API Compatibilities.
No mention of the fact that Ollama is about 1000x easier to use. Llama.cpp is a great project, but it's also one of the least user friendly pieces of software I've used. I don't think anyone in the project cares about normal users. I started with Ollama, and it was great. But I moved to llama.cpp to have more up-to-date fixes. I still use Ollama to pull and list my models because it's so easy. I then built my own set…
Easier than what?
I came across LM Studio (mentioned in the post) about 3 years ago before I even knew what Ollama as. It was far better even then.
For most users that wanted to run LLM locally, ollama solved the UX problem. One command, and you are running the models even with the rocm drivers without knowing. If llama provides such UX, they failed terrible at communicating that. Starting with the name. Llama.cpp: that's a cpp library! Ollama is the wrapper. That's the mental model. I don't want to build my own program! I just want to have fun :-P
Llama.cpp now has a gui installed by default. It previously lacked this. Times have changed.
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.
For most users that wanted to run LLM locally, ollama solved the UX problem. One command, and you are running the models even with the rocm drivers without knowing. If llama provides such UX, they failed terrible at communicating that. Starting with the name. Llama.cpp: that's a cpp library! Ollama is the wrapper. That's the mental model. I don't want to build my own program! I just want to have fun :-P
Llama.cpp now has a gui installed by default. It previously lacked this. Times have changed.
It makes a bunch of decisions for you so you don't have to think much to get a model up and running.