Refurbished Laptops & Desktops for Local AI
12 refurbished laptops, desktops & mini PCs for running Ollama, LM Studio, Llama 3, Qwen, and Mistral locally — no cloud, no API key. Ships same day from Reno, NV.
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12 devices · Mini PC
Mini PCDell
Dell OptiPlex 3080 Micro MFF Intel Core i5-10500T 2.3GHz 16GB RAM 256G NVMe W11P
Mini PCHP
WRTY 2028 /HP Elite Mini 800 G9 i3-12100T 16GB 256GB NVMe SSD WIFI BT Win 11 Pro
Mini PCDell
Dell OptiPlex 3000 Micro PC Intel Core i5-12500T 16GB DDR4 256GB NVMe | Win 11 P
Mini PCHP
HP PRO MINI 400 G9 | Core i5-12500T | 16GB | 256GB NVMe SSD | Win 11 Pro +AC Adp
Mini PCDell
Dell OptiPlex 5000 Micro MFF i7-12700T 1.4GHz 16GB 512GB SSD WiFi BT Win 11 Pro
Mini PCOther
Game Mini PC Beelink EQR6 AMD Ryzen 9 6900HX RAM 24GB SSD 1TB Dual Gigabit Win11
Mini PCDell
WRTY 2029 /Dell Pro Micro Plus QBM1250 Business PC Ultra 5 235 16GB 1TB W 11 P
How to run AI locally
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Install Ollama
Free. ollama.com. 2 minutes.
Pull a model
ollama run llama3
Chat privately
Nothing leaves your machine.
Common questions
What laptop do I need to run Llama 3.1 locally?
To run Llama 3.1 8B comfortably, you need at least 16GB RAM. For Llama 3.1 70B, you need 32GB+ RAM or a GPU with 16GB+ VRAM. Apple Silicon MacBooks (M1/M2/M3/M4) with 16GB unified memory run 8B models at 20–40 tokens/sec with no setup beyond installing Ollama.
Can I run local AI on a laptop without a GPU?
Yes. CPU-only inference works well for 7B–8B models on any laptop with 16GB+ RAM. Expect 5–15 tokens/sec, which is readable in real time. For faster speeds, a laptop with a discrete NVIDIA GPU (6GB+ VRAM) or Apple Silicon is recommended.
How much RAM do I need to run AI models locally?
8GB RAM is the minimum — runs Phi-4 Mini and Llama 3.2 3B only. 16GB RAM runs Llama 3.1 8B and Qwen3 7B at usable speeds. 32GB runs Qwen2.5 14B and 32B Q4 models. 64GB runs 70B models at full quality.
Do desktops and mini PCs work for local AI?
Yes. A Dell OptiPlex or Intel NUC with 16GB RAM runs 7B models well. Gaming desktops with RTX GPUs (8GB+ VRAM) handle 13B–32B models at 20–50 tokens/sec.
Is Apple Silicon (M1/M2/M3/M4) good for running local AI?
Apple Silicon is excellent for local AI. Unified memory means the GPU and CPU share the same RAM pool, so a 32GB M2 Pro can offload a full 32B model to the GPU. Metal acceleration is automatic via Ollama. M1 16GB runs 8B models at 20–30 tokens/sec. M2/M3/M4 32GB runs 32B Q4 models at 15–25 tokens/sec.
How do I start after buying a device?
Install Ollama from ollama.com (free, 2 minutes). Open Terminal and run: ollama run llama3.1:8b — it downloads the model and starts automatically. For a ChatGPT-style interface, install LM Studio from lmstudio.ai. No cloud account, no subscription, no data leaving your machine.