GPT4All - ChatGPT That Actually Respects Your Privacy

GPT4All from Nomic AI runs models directly on your laptop. No data leaves your machine. No subscription fees. No "oops we're down" messages when you're trying to work.

I've been using it for months now, and here's the deal: it's not as smart as GPT-4, but it's good enough for most tasks, and it keeps your code reviews, personal notes, and sensitive documents off some corporation's servers. Plus, once you download a model, you're done paying forever.

It's got 72,000+ GitHub stars and 250,000+ active users, so you're not downloading some weekend project that'll die in 6 months. The Discord is actually active - people help each other instead of just posting memes.

What Actually Works

• LocalDocs for your project docs - Point it at your codebase docs and it'll actually answer questions about your own code without leaking shit to OpenAI. Handles PDFs, Word docs, text files. Warning: embeddings vanish randomly so back them up.
• DeepSeek R1 models - Finally got some decent reasoning models that don't give you gibberish when you ask about code logic.
• Rubber duck debugging - Not brilliant, but catches the obvious bugs you miss at 2am. The Python bindings let you automate this.
• Compliance-friendly writing - Banks and government contractors can use this without their security team having a heart attack. Zero data collection.

What Sucks (Let's Be Honest)

• Initial model downloads take forever - We're talking 4GB+ files that love to timeout on shitty wifi. Check the troubleshooting wiki for download issues.
• Some models are complete garbage despite having impressive names like "UltraChat Supreme" - The "GPT-OSS 20B" model straight up crashes the app on load. "WizardLM-13B-Uncensored" gives you random poetry when you ask for Python code. Browse Simon Willison's model tests before downloading random shit.
• Memory usage is higher than advertised - Plan for 12GB+ if you want to run anything decent. The official specs are optimistic.
• No streaming responses - You ask a question and wait 30+ seconds for the full answer. GitHub issue #709 shows this has been a problem since 2023 - streaming exists but it's fake streaming that generates everything first then displays it.
• First response after loading takes forever - Models need to "warm up" and it's annoying. This is a known llama.cpp limitation, not specific to GPT4All.

The truth is, I switched to GPT4All after getting burned by OpenAI's API going down during a client demo. Now I've got local models that work even when the internet doesn't, and my client conversations stay private.

What They Don't Warn You About

Windows: 200MB installer downloads fine, then you wait 45 minutes for a 4GB model on corporate WiFi that's configured by sadists. Will timeout twice, guaranteed. There's an ARM version for Snapdragon laptops that nobody owns.

macOS: Works great on M1/M2 Macs with the DMG installer. Intel Macs are slow as hell but functional. Doesn't work on older macOS versions, found out the hard way. There's also a Homebrew option if you prefer that.

Linux: .run installer works if you trust random binaries. I compile from source because I'm not running mystery executables on my machine. Flathub version exists but updates lag behind. Breaks on Debian 12+ with some "SingleApplication" bullshit - Ubuntu works fine.

Your First Model Download Will Suck

App defaults to "Meta-Llama-3-8B-Instruct" - 4.66GB that takes forever on anything slower than fiber. Hotel WiFi? Forget it. I've watched downloads hit 95% then die with a timeout error.

Try "Nous Hermes 2 Mistral 7B" first - 3.8GB and decent quality. Half the models are trash anyway, so don't waste 2 hours downloading "UltraChat Supreme" only to find out it can't count to 10.

Hardware: The Stuff That Actually Matters

• 16GB RAM or suffer - They claim 8GB works but it's painful. Your laptop will swap constantly and take 3x longer for everything.
• SSD required - Don't even try this on a spinning drive from 2015. Models take forever to load from slow storage.
• GPU helps but isn't magic - Vulkan support speeds things up on decent GPUs. My RTX 3070 makes it usable; integrated graphics barely help.
• Fiber internet for downloads - Model downloads will break your soul on slow connections. Download resumption exists but it's buggy.

Memory: They're Lying About the Requirements

"4GB model" my ass - it'll eat 6GB of RAM plus another 2GB for the app. On 8GB laptops you'll hit swap and everything turns to molasses. Learned this during a client demo when the whole thing locked up. Had to force quit, restart, and pretend it was "planned maintenance." Now I don't demo on anything with less than 16GB.

Python Integration (If You're Into That)

pip install gpt4all

from gpt4all import GPT4All
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf")
with model.chat_session():
    response = model.generate("Why is my local LLM so slow?", max_tokens=1024)

The Python bindings actually work well. Much better than the early days when everything was broken. You can integrate this into existing apps without too much pain. Works with LangChain, LlamaIndex, and other LLM frameworks. The API documentation is actually readable, unlike some projects. There's also a Docker API server if you want to run it headlessly.