Runs 8–14B models — Refurbished devices
55 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.
Filter by AI capability
55 devices · Runs 8–14B models
MacBookApple
Apple MacBook Pro 13"2020 M1 8CPU8GPU 3.2GHz 16GB 512GB Monterey A2338/MYDA2LL/A
Dell
Dell Latitude 7640 16" FHD+ Intel Core i7-1365U 1.80GHz 32GB 512GB SSD+Charger
Dell
Dell Precision 5570 15.6" FHD+ i7-12800H 2.4GHz 32Gb 512GB RTX A1000 4GB W11P+PA
Dell
Dell Precision 5570 15.6"FHD+ i7-12700H 2.3GHz 32Gb 512GB RTX A1000 4GB WRTY2028
MacBookApple
Apple MacBook Pro 16" A2485 2021 M1 Pro 3.2GHz 10 CPU/16GPU 16GB 512GB Silver
Dell
Dell Precision 5560 15.6"FHD+ i9-11950H 2.6GB 64Gb 1TB SSD NVIDIA A2000 +Charger
Lenovo
Lenovo Slim 7 14IMH9 14" WUXGA OLED Touch Ultra 7 155H 32GB 1TB Intel Arc Win11h
How to run AI locally
Pick a device
Filter by tier, brand, or type.
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.