Can I Run Local AI Models on My Home Computer?
A Quick Guide to Home Server
Requirements in 2026.
Yes, for most people, running AI at home is very achievable in 2026. It does come with real hardware and budget considerations, and memory prices have been climbing, so it's worth knowing what you need before you buy anything. This guide explains what hardware matters, whether your current computer qualifies, and how to get started without writing a single line of code.
One note before we begin: running a model locally keeps your prompts on your own machine, but the app around it can still make network connections for updates or telemetry. Privacy depends on how you set things up.
What kind of hardware do you actually need?
The single most important number is memory. To run a model comfortably, your graphics card's memory (VRAM), or your computer's shared "unified" memory, needs to hold the model plus some headroom for the conversation itself.
| Hardware tier | VRAM or unified memory | Comfortable model size | Typical cost |
|---|---|---|---|
| Entry level | 8–12GB VRAM, or 16GB unified | 7B–8B parameter models | Used GPU ~$150–$250; Mac from ~$500 <! data-preserve-html-node="true"-- VERIFY current used prices --> |
| Sweet spot | 16–32GB VRAM, or 32–48GB unified | 13B–32B parameter models | Used GPU ~$300–$600; Mac from ~$1,000 <! data-preserve-html-node="true"-- VERIFY --> |
| High end | 48GB+ VRAM, or 64–128GB unified | 70B-class models | Multi-GPU builds, high-memory Macs, or a dedicated box like Companion Core |
Consumer GPUs vs. enterprise hardware for large models
For everyday chat, writing, and coding help, modern consumer graphics cards and Apple Silicon handle models up to about 30 billion parameters well.
Larger models are where memory runs out. A 70B model needs roughly 40GB of memory at 4-bit quantization and about 75GB at 8-bit, before leaving room for long conversations. The largest single consumer graphics card today has 32GB, so most home PCs can't fit a 70B model on one card.
You don't need data-center hardware to get there, though. Your options are:
- Two or more graphics cards working together, which takes more setup and more power.
- A high-memory Mac with 64GB or more of unified memory.
- A unified-memory machine built for it. Companion Core uses an AMD Ryzen AI Max+ 395 with up to 128GB of unified memory, enough to run 70B-class models on the device itself.
Is a local AI setup worth the cost?
It depends on what you spend now and what hardware you need. Be wary of anyone promising a fixed payback period.
If you pay around $20 a month for an AI subscription, that's $240 a year. Repurposing a computer you already own, or adding a used graphics card for a few hundred dollars, can pay off within one to two years. A dedicated machine costing thousands won't pay for itself on a single $20 subscription alone.
The math improves quickly as your spending grows. If you pay for several AI tools, for a premium tier like ChatGPT Pro at $200 a month, or for heavy pay-per-use API calls, a dedicated machine can pay for itself in one to two years. Heavy API users, such as people analyzing files daily or running long conversations, feel the savings fastest because local use has no per-token charges.
Beyond the money, local AI ends subscription fatigue and keeps your prompts and files on your own hardware, as long as you check your app's update and telemetry settings.
For a worked example with real numbers, see our post When Ownership Beats Subscriptions: The Family Tech Math.
The easiest way to get started without coding
You don't need to touch a terminal. These free desktop apps let you browse models, download them with a click, and start chatting:
| App | What it is | Best for beginners who… |
|---|---|---|
| LM Studio | Desktop app for macOS, Windows, and Linux | Want to browse models easily and see memory requirements before downloading |
| Jan | Open-source desktop app | Want a ChatGPT-style interface with chat history and file uploads, fully offline |
| Ollama | Desktop app for macOS and Windows, plus a command line | Want a simple chat window now, with room to grow into developer tools later |
| GPT4All | Lightweight desktop app | Want the simplest possible starting point for basic chat |
For most beginners, LM Studio is the friendliest first step.
If you want more than chat, such as private file storage, photo backup, and a catalog of one-click local apps alongside your AI models, Companion Hub is free and runs on Mac, Windows, and Linux.
Want hardware built for this?
If your current computer falls short, or you want a quiet machine that runs 70B-class models without a multi-GPU build, Companion Core arrives ready to go. It runs every Companion Hub app and local AI models on an AMD Ryzen AI Max+ 395 with up to 128GB of unified memory.
Companion Core is on Kickstarter now, at the lowest price it will ever have:
- Core 64 — $3,200, Kickstarter only
- Core 128 — $5,400, Kickstarter only
Kickstarter pricing ends with the campaign. After that, the Core sells at a higher price on our website.
Back Companion Core on Kickstarter →
Frequently Asked Questions
What is the minimum GPU I need? A graphics card with at least 8GB of VRAM can run small 7B–8B models. On a Mac, 16GB of unified memory is a comfortable minimum; 8GB works only for the smallest models.
How much storage do I need? Plan for 50–200GB of free SSD space. A small model takes about 5GB, while a 70B model takes about 40GB, and most people keep several models installed.
Can my home PC run a 70B model? Usually not on a single graphics card. A 70B model needs about 40GB of memory at 4-bit quantization. You'll need multiple GPUs, a Mac with 64GB or more of unified memory, or a machine like Companion Core with up to 128GB of unified memory.
Does local AI guarantee complete privacy? No. Running locally keeps your prompts and files off a company's servers, but the app may still check for updates or send usage data. Review your app's settings to see what is switched on.
How much does Companion Core cost? On Kickstarter, Core 64 is $3,200 and Core 128 is $5,400. Those prices are Kickstarter-only; the Core will cost more on our website after the campaign. Back it on Kickstarter.
Ready to take control of your data?
Stop renting your AI and start owning it. Check your current computer against the tiers above, install a free app like LM Studio or Jan, and try a model today. The hardware barrier is lower than it has ever been, and private, subscription-free AI is within reach for far more people.
