llama.cpp WebUI launched : Free, Private Local ChatGPT

There’s a new shake-up in the local LLM scene, and this one’s big.

Llama.cpp, the famously fast local inference engine that made it easy to run Meta’s Llama models on your laptop, now has a Web UI. In plain words: you can now chat with open models through a clean browser interface, just like ChatGPT, but completely offline and completely free.

And yes, that means tools like Ollama might finally have a serious rival.

So, what exactly is Llama.cpp?

If you’ve ever played around with local LLMs, you’ve probably heard of it. Llama.cpp is an open-source C++ implementation that allows you to run large language models locally, directly on your machine, without GPUs or cloud dependencies. It’s light, efficient, and ridiculously optimized, that’s why it’s used under the hood in half the “offline AI” projects out there.

It’s the backbone for countless small tools that want to bring AI inferencing to edge devices. The whole idea was: you shouldn’t need a data center to chat with an AI. Just your laptop, a GPU, and a model file.

Until now though, Llama.cpp was more of a CLI-only experience, powerful, but not exactly user-friendly. You had to fiddle with command-line commands, ports, models, and environment variables. The new WebUI changes all that.

What’s new with the WebUI?

The official Llama.cpp WebUI gives you a ChatGPT-like interface right in your browser, running locally. Once you launch it, you can open localhost:8080 (or any port you set), type your prompts, and chat, no sign-ins, no internet, no API calls.

Here’s what stands out:

• Minimal and fast UI, it just works.
• Token speed on local CPUs is surprisingly good (people are reporting 60+ tokens/sec).
• It even supports file uploads if the model you’re using handles that (for instance, models fine-tuned for RAG or PDF parsing).
• Full context view with input/output logs, so you can see exactly how your model processes text.

Llama.cpp vs. Ollama: who’s winning now?

Ollama has been the go-to choice for people who wanted an easy local ChatGPT-like setup. It comes with model management, automatic downloads, and a web interface (if you use extensions). But Ollama also runs as a background service, and it’s not as transparent about what’s happening under the hood.

Llama.cpp, on the other hand, is open to the bone, you see every command, every model file, every bit of activity.

Now with the WebUI, that gap in accessibility is gone.
You get:

• The same kind of browser interface,
• More direct control,
• Lower resource overhead,
• And no hidden telemetry or background services.

In short: Ollama’s convenience meets Llama.cpp’s transparency. If you care about privacy and control, this release makes Llama.cpp the clear winner.

How to install and run Llama.cpp WebUI

Follow this video for clear step by step guide

You can run any gguf model from huggingface, just get its id

Performance and experience

The speed is genuinely impressive.

I demoed Gemma 3 1B GGUF running locally at 60.5 tokens per second, answering “Tell me about India” in under a second.

You can monitor context size, output rates, and even attach small text files. For now, some features like PDF or image attachments depend on the model you use, but the base system supports it.

Why this matters

We’ve been slowly moving toward local-first AI, where you don’t need a server halfway across the world to generate a paragraph. The release of the Llama.cpp WebUI is a turning point.

It makes private AI actually usable.

You don’t need to be a terminal wizard anymore. You can just open a browser and talk to your local model, no data leaks, no subscriptions, no throttling.

It’s the kind of move that might look small now but sets a big precedent. For years, “running your own ChatGPT” was a messy dream for developers. Now it’s a two-line command.