LM Studio - Run AI Models On Your Own Computer

Why I Switched From ChatGPT to Running Models Locally

I got sick of my ChatGPT bills hitting $50/month, so I tried running models locally. LM Studio makes this actually possible without learning 47 command-line tools.

What is this thing actually?

Here's what nobody tells you: LM Studio is probably the easiest way to run AI models on your own computer. Download the app, click a model, and it works. Mostly.

The interface looks clean, kind of like ChatGPT but slower and without the constant internet requirement. You download GGUF format models which are basically compressed AI brains that actually fit on your hard drive.

LM Studio Interface Screenshot

Setup takes 20 minutes, not 2 minutes like they imply. But once it's running, you can chat with models offline. No internet = no data leaving your machine. That's the whole point.

The privacy thing isn't bullshit

Everything runs on your computer. Your weird questions about code, personal stuff, or whatever - none of it gets sent to OpenAI's servers. For companies handling sensitive data, this is huge. No compliance nightmares, no "did our API calls just train their next model" paranoia.

Your conversations don't leave your machine. ChatGPT logs everything you say. For sensitive stuff, this matters.

The offline thing is real. Once models are downloaded, you can literally disconnect from wifi and keep using it. Handy when internet craps out or you're on a plane.

Your laptop will probably hate you

They say 16GB minimum but that means it'll swap to death and run like molasses. 32GB is where it becomes usable.

If you have an NVIDIA GPU with decent VRAM, models run much faster. Apple Silicon Macs work well too - M2/M3 MacBooks handle this shit way better than I expected.

Your laptop will heat up and fans will spin. This isn't like browsing Twitter - you're running actual AI inference locally. Plan for extra electricity usage too. GPU inference can triple your system's power draw.

Drop-in replacement for ChatGPT

The OpenAI-compatible API is clutch. Point existing ChatGPT tools at http://localhost:1234 and they work with local models. I've tested this with VS Code extensions, Continue.dev, and AutoGen scripts.

There's also some Model Context Protocol support they added in 2025 that connects models to external tools. Still figuring out what that actually enables in practice.

Which Local AI Tool Should You Actually Use?

Feature	LM Studio	Ollama	Jan AI	GPT4All	Llama.cpp
How it looks	Actually pretty decent	Terminal only (some people like that)	Desktop app but crashes	Basic but works	You're on your own
Setup	Download, install, works	One command usually works	Pain in the ass	Dead simple	Compile it yourself, good luck
Getting models	Click and download	`ollama pull llama3`	Slow GUI downloads	Pick from built-in list	Hunt down GGUF files manually
Memory usage	Uses what it needs	Depends on the model	Memory hog from hell	Easy on RAM	Set everything yourself
GPU stuff	Usually works fine	Works if drivers don't suck	Maybe works, maybe doesn't	Hit or miss	Works great when you figure it out
API server	Drop-in OpenAI replacement	Built-in and solid	Need plugins for basic features	Barely functional	Build your own
Multiple GPUs	Actually handles this	Single GPU, deal with it	Nope	Nope	Yes but you better know what you're doing
Stability	Crashes sometimes	Rock solid	Crashes constantly	Boring but stable	Solid as a rock when running
Community	New but growing fast	Reddit darling	Small but vocal	Decent user base	Old school hackers only

What You Need to Know Before Installing

The "16GB minimum" they advertise is technically true but practically useless. Here's what actually works based on testing various setups.

Real Hardware Requirements

Download LM Studio from their website - it's just a regular app installer. The hardware requirements they list are optimistic:

What they say vs reality:

16GB RAM: Will swap to death. Models load but run like fucking molasses.
32GB RAM: Actually usable for most stuff. Sweet spot for 7B models.
64GB RAM: Run big models without wanting to throw your laptop out the window.

Storage reality check:

Each model is 4-12GB. Qwen models are huge.
SSD is non-optional. HDDs will make you hate life.
Budget 100GB+ storage if you want to try different models.

Platform gotchas:

Mac: M2/M3 work great with Metal acceleration. Intel Macs are slow.
Windows: Works fine but Windows Defender flags model downloads as suspicious.
Linux: No surprises, just works if your GPU drivers don't suck.

The Model Download Reality

GGUF Format Overview

The model catalog looks impressive until you realize:

Popular models (Llama, Qwen) download fast
Obscure models download at 56k speeds or fail entirely
"Quantized" versions trade quality for speed - Q4 models are noticeably dumber than Q8

Model management features that actually work:

One-click downloads (when they don't timeout)
Shows file sizes before downloading (crucial for planning storage)
Can pause/resume downloads (lifesaver for big models)
Automatic hardware detection usually picks the right format

Settings You'll Actually Change

Most people never touch the advanced settings, which is fine. But if you're curious:

Temperature: Higher = more creative/weird responses. Start with 0.7.
Context length: How much conversation history the model remembers. Longer = slower.
GPU layers: How much of the model runs on GPU vs CPU. Auto-detect works most of the time.

The OpenAI API server is clutch - runs on localhost:1234 by default. Point any ChatGPT-compatible tool at it and boom, local AI.

Commercial Use (Finally Free)

They removed the commercial license fee in July 2025, which was a huge relief. Previously you needed to pay for work use.

LM Studio for Teams adds some sharing features but it's early days. Most teams just use the regular version and sync configs via Slack or whatever.

The privacy angle is real - everything runs locally, nothing phones home unless you explicitly connect to their hub thing (which is optional).

Cost Reality Check

"Free" software but your electricity bill will notice. GPU inference is power-hungry. My RTX 4070 pulls ~200W running models vs ~50W idle. Plan accordingly.

Large models will heat up your laptop and spin fans to jet engine levels. Fine for desktop workstations, annoying for ultrabooks.

Shit people keep asking me

Is there some bullshit subscription I'm missing?

It's actually free now.

They removed the commercial license fee in July 2025. Previously you had to pay for work use, which sucked. No registration, no credit card, just download and use it.

Will this work on my 2019 MacBook or should I just give up?

Depends how ancient we're talking. 16GB RAM is the bare minimum but models will run slow as hell. 32GB is where it becomes actually usable. If you have 8GB or less, don't even bother trying.GPU helps a lot

even old GTX cards speed things up. But CPU-only works, just very slowly.

Why is this so fucking slow compared to ChatGPT?

Because you're running the AI model on your laptop instead of a datacenter with $50,000 GPUs. Local models are 2-5x slower than cloud APIs. That's the trade-off for privacy and no monthly bills.Q4 quantized models are faster but noticeably dumber. Q8 models are smarter but slower. Pick your poison.

Does this actually work offline?

Yes, once models are downloaded. Download takes forever the first time (models are 4-12GB) but then you can disconnect wifi and it still works. Handy for planes or when internet craps out.

Which models are actually good?

Qwen models are solid for general chat. Gemma works well for coding questions. Avoid the really small models (1B-3B) unless you're desperate

they're pretty dumb.Start with Llama 3.1 8B
good balance of speed and intelligence.

Can I use this with my existing ChatGPT tools?

Yeah, the OpenAI API compatibility actually works. Change the endpoint URL from api.openai.com to localhost:1234 and most tools work fine.I've tested it with VS Code extensions, writing tools, and automation scripts. Some features won't work (no DALL-E obviously) but chat stuff works.

Should I just stick with ChatGPT? This seems like a lot of work

Depends what pisses you off more:

Privacy paranoia? Use LM Studio.
Monthly bills? LM Studio saves money long-term.
Need it fast? ChatGPT is faster.
Laptop sounds like jet engine? Maybe stick with cloud.

I use both - LM Studio for personal/sensitive stuff, ChatGPT when I need speed and don't care about privacy.

My laptop sounds like a jet engine when running models. Is this normal?

Unfortunately yes. Running AI models locally is computationally intensive. Your laptop will heat up and fans will spin at max RPM. This is physics, not a bug.Desktop computers handle this better than laptops. Ultrabooks suffer the most.

How much will this cost me in electricity?

GPU inference is power-hungry. My RTX 4070 pulls ~200W running models vs ~50W idle. If you run models all day, expect your electricity bill to notice.Rough math: ~$20-50/month in electricity if you use it heavily. Still cheaper than ChatGPT subscriptions.

Does Windows Defender keep flagging the models as malware?

Yeah, it's annoying. The model files trigger heuristics because they're large binary blobs from the internet. You'll need to add exceptions or disable real-time protection during downloads.This happens with all local AI tools, not just LM Studio.

Is the privacy thing actually real or just marketing?

It's real. Everything runs on your machine. No network calls to external servers (unless you enable their optional hub features). Your conversations stay local. Much better than ChatGPT which definitely logs everything you say.