Ollama vs. LM Studio vs. ?

Hi everyone, I’ve been experimenting with local LLMs on my 48 GB RAM MacBook Pro and I’m still trying to figure out what the best setup is. Ollama feels very fast, which I really like. The problem for me is the GUI side. Open WebUI works, but it feels pretty heavy, and the extra RAM usage is a bit annoying on a machine where I’d rather leave as much memory as possible for the model/context. I’ve also tried Docker and OrbStack and noticed quite a bit of overhead. LM Studio feels much more lightweight in terms of RAM and is very convenient, but in my testing it seems a little slower. It’s also closed source. What I’m basically looking for is something simple: low overhead, good tok/s, as much context as possible, ideally open source, and the ability to access it from other devices on my home network. Is there a lightweight GUI for Ollama that I’m missing? Or would something like llama.cpp + llama-server be a better way to do this? I’ve actually never used llama.cpp myself. I came across it while researching this, and people in another Ollama vs. LM Studio thread seemed to recommend it quite a bit, so now I’m wondering whether it’s worth trying. I’m mainly interested in what people are actually using for this kind of setup. I don’t need a huge feature-packed UI, just something lightweight that works well. EDIT: I probably didn’t explain my question very well. I’m mainly looking for a lightweight GUI/frontend, not another inference backend. I like Ollama, but Open WebUI feels quite heavy for my use case. So I’m wondering what people use on top of Ollama instead. And if running llama.cpp directly has advantages in terms of performance/overhead, is there a good lightweight GUI for llama-server? submitted by /u/Plus-Contribution203 [link] [comments]

Source: r/ollama | 2026-09-18

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