Thread by @aiwithjainam

This feels like the early Internet moment for AI.

For the first time, you don’t need a cloud account or a billion-dollar lab to run state-of-the-art models.

Your own laptop can host Llama 3, Mistral, and Gemma 2 full reasoning, tool use, memory completely offline.

Here are 5 open tools that make it real:

1. Ollama ( the minimalist workhorse )

Download → pick a model → done.

✅ “Airplane Mode” = total offline mode
✅ Uses llama.cpp under the hood
✅ Gives you a local API that mimics OpenAI

It’s so private I literally turned off WiFi mid-chat still worked.

Perfect for people who just want the power of Llama 3 or Mistral without setup pain.

2. LM Studio ( local AI with style )

This feels like ChatGPT but lives on your desktop LOCALLY!

You can browse Hugging Face models, run them locally, even tweak parameters visually.

✅ Beautiful multi-tab UI
✅ Adjustable temperature, context length, etc.
✅ Uses Ollama as a backend

You can even see CPU/GPU usage live while chatting.

3. AnythingLLM ( makes local models actually useful )

Running models is cool… until you want them to read your files.

AnythingLLM connects your local model (via Ollama) to your PDFs, notes, and docs all offline.

✅ Works with Ollama
✅ 100% local embeddings + retrieval
✅ Build RAG setups and agents with no cloud calls

It’s like having your own private ChatGPT trained on your personal knowledge base.

4. llama. cpp ( the OG powerhouse )

This is what powers most of the above tools.

Pure C++ speed, extreme efficiency, runs on anything from a MacBook to a Raspberry Pi.

Not beginner-friendly, but if you want control (quantization, model variants, hardware tuning) this is it.

5. Open WebUI ( your own ChatGPT clone )

Run it locally in your browser, plug in Ollama or LM Studio as backend, invite teammates.

✅ Multi-user chat
✅ Memory + history
✅ All local, nothing leaves your device

Basically, it’s like hosting your own private GPT server beautifully designed.

Why run LLMs locally?

→ No data leaves your machine
→ Works offline
→ Free once downloaded
→ You own the weights, not some API

Yes, the trade-off is speed and hardware, but with quantized models (Q4/Q5/Q6), even 7B–13B runs fine on a MacBook.

Running AI locally isn’t about paranoia it’s about sovereignty.
Owning your compute, your data, your model.

In a world obsessed with cloud AI, local AI is the real rebellion.

Master AI and future-proof your career.

Our newsletter, The Shift, delivers breakthroughs, tools, and strategies you won't find anywhere else – 5 days a week.

Subscribe today:

Plus, get access to 2k+ AI Tools and free AI courses when you join.theshiftai.beehiiv.com/subscribe