What Should I Buy to Run AI Locally?
Answer four quick questions — or browse curated builds by price — and get exactly what to buy for local LLMs: DIY part lists, plug-and-play mini-PCs, and laptops, each with the models it can actually run.
2026 GPU/DRAM prices are volatile — always check the live listing.
What do you want to run?
Pick everything that applies — it sets the minimum model class you'll need.
Every curated build
Open Browse by price for each build’s parts list, what it runs and where to buy it.
| Build | Type | Price tier | Memory | Price |
|---|---|---|---|---|
| Used RTX 3060 12GB Starter The cheapest way into local AI that doesn't dead-end: 12GB VRAM runs every 7–8B model fast and stretches to 13–14B at tighter quantization. | DIY parts build | Under $500 | 12 GB VRAM | $495 |
| Apple Mac mini M4 (16GB) The cheapest silent, always-on AI box: 16GB unified memory runs 7–8B models well, in a palm-sized machine that idles at a few watts. | Mini-PC / AI station | $500–$1,000 | 16 GB unified memory | $599 |
| Beelink SER9 (32GB, Ryzen AI 9) The budget Windows/Linux mini-PC pick: 32GB of unified memory runs 13–14B models in a quiet, compact box that doubles as a daily desktop. | Mini-PC / AI station | $500–$1,000 | 32 GB unified memory | $859 |
| RTX 5060 Ti 16GB Budget Build The cheapest all-new-parts 16GB build: warranty on everything, low power draw, and 16GB covers 14B-class coder models comfortably. | DIY parts build | $500–$1,000 | 16 GB VRAM | $985 |
| RTX 4060 Ti 16GB Value Build The classic value pick: 16GB of new-card VRAM covers 14B coder and vision models with headroom, on a modern AM5 platform you can upgrade for years. | DIY parts build | $1,000–$2,000 | 16 GB VRAM | $1,090 |
| RTX 4060 Gaming Laptop (8GB VRAM) The budget portable option with a real NVIDIA GPU: CUDA support and 8GB VRAM run 7–8B models anywhere, including tools that require NVIDIA. | Laptop | $1,000–$2,000 | 8 GB VRAM | $1,099 |
| Used RTX 3090 24GB Value King The best VRAM per dollar in 2026: a used RTX 3090's 24GB runs 32B models entirely in VRAM and even LoRA fine-tunes 7–8B models. | DIY parts build | $1,000–$2,000 | 24 GB VRAM | $1,240 |
| Apple Mac mini M4 Pro (24GB) The quiet 24/7 pick: M4 Pro bandwidth (273 GB/s) makes 14B models feel responsive, and it sips power as a always-on home AI server. | Mini-PC / AI station | $1,000–$2,000 | 24 GB unified memory | $1,399 |
| Minisforum MS-A2 (96GB) Maximum memory capacity per dollar: 96GB fits 70B Q4 — the cheapest single box that can load one — as long as you accept CPU-class speeds. | Mini-PC / AI station | $1,000–$2,000 | 96 GB unified memory | $1,599 |
| Beelink GTR9 Pro (128GB, AI Max+ 395) The unified-memory sweet spot: Strix Halo's 256 GB/s over 128GB runs 70B Q4 at usable speeds and giant MoE models no consumer GPU can hold — 30–40% cheaper than a comparable Mac Studio. | Mini-PC / AI station | $1,000–$2,000 | 128 GB unified memory | $1,899 |
| MacBook Pro 14" M4 (24GB) The balanced AI laptop: 24GB of unified memory quietly runs 13–14B models on battery — no discrete-GPU laptop at this price can load models that size. | Laptop | $1,000–$2,000 | 24 GB unified memory | $1,999 |
| GMKtec EVO-X2 (128GB, AI Max+ 395) Same 128GB Strix Halo platform with the most aggressive sustained-power tuning — the fastest of the AI-station boxes when noise isn't a constraint. | Mini-PC / AI station | $2,000–$5,000 | 128 GB unified memory | $2,349 |
| RTX 4090 24GB Enthusiast The fastest single-card build most people should buy: 24GB at 1,008 GB/s chews through 32B models and runs 70B with offloading. | DIY parts build | $2,000–$5,000 | 24 GB VRAM | $2,590 |
| Dual RTX 3090 48GB (70B-class) The cheapest genuinely fast 70B rig: two used RTX 3090s pool 48GB of VRAM, so 70B Q4 runs fully on GPU instead of crawling through system RAM. | DIY parts build | $2,000–$5,000 | 48 GB VRAM | $2,870 |
| MacBook Pro 16" M4 Max (48GB) The most capable AI laptop you can buy: 48GB unified at 546 GB/s runs 32B models fast and fits 70B Q4 — capabilities no PC laptop matches at any wattage. | Laptop | $2,000–$5,000 | 48 GB unified memory | $3,999 |
| Dual RTX 4090 48GB AI Workstation The no-compromise workstation: dual RTX 4090s give 48GB of the fastest VRAM money reasonably buys, for 70B inference at interactive speeds and serious fine-tuning. | DIY parts build | $5,000+ | 48 GB VRAM | $5,040 |
Frequently asked questions
How much does a local AI PC cost in 2026?
A usable starter build with a used RTX 3060 12GB lands under $500 and runs 7–8B models. The sweet spot is $1,000–1,300 — an RTX 4060 Ti 16GB build or a used RTX 3090 24GB build — which covers 14–32B models. Around $2,400–2,900 (RTX 4090 or dual RTX 3090) you can run 70B-class models at Q4.
What's the cheapest way to run a 70B model locally?
Two paths: a dual used RTX 3090 build (~$2,900, 48GB pooled VRAM, fastest) or a 128GB unified-memory mini-PC like the Beelink GTR9 Pro (~$1,899) — cheaper and silent, but roughly a quarter of the token speed because of its 256 GB/s memory bandwidth.
Mini-PC vs building your own for local AI — which is better?
DIY wins on speed per dollar: discrete GPUs have 3–7× the memory bandwidth of unified-memory boxes. Mini-PCs win on capacity per dollar, noise, and convenience — a 128GB Strix Halo box fits 70B+ models that no consumer GPU can hold. Buy DIY for interactive speed, mini-PC for big-model capacity or a quiet office.
Is a used RTX 3090 still worth it in 2026?
Yes — at ~$650–750 used it remains the best VRAM per dollar. 24GB runs 32B models at Q4 fully in VRAM, and its 936 GB/s bandwidth is close to an RTX 4090. Buy from a seller with returns and stress-test the memory on arrival.
Are Macs good for running local LLMs?
Apple Silicon is excellent for quiet, always-on setups: unified memory lets a Mac mini M4 Pro or MacBook Pro M4 Max load models a same-price GPU can't fit. Token speed is lower than a discrete NVIDIA card, and the M4 Max now tops out at 96GB unified memory — enough for 70B Q4, not the largest MoE models.
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