Best GPU for Local AI (2026)
Cornerstone WikiWayne guide: Best GPU for Local AI (2026). Open-weight, practitioner-tested local AI.
Open-weight models, local inference stacks, VRAM planning, and homelab setups for running AI on your own hardware.
Local AI topical hubCornerstone WikiWayne guide: Best GPU for Local AI (2026). Open-weight, practitioner-tested local AI.
Shopping the secondary market without overspending on VRAM you cannot use.
Load checkpoints, wire KSampler, export PNGs locally.
Cornerstone WikiWayne guide: ComfyUI Local Stable Diffusion Guide. Open-weight, practitioner-tested local AI.
What `-ngl` / GPU layer sliders actually do.
Compose services for local chat without cloud relay.
Quant-specific VRAM bands for Meta Llama 3 8B class models.
Step-by-step Ollama install paths for the three major desktop OS families.
Import GGUF and tune narrative sampling locally.
Cornerstone WikiWayne guide: KoboldCpp Local LLM Guide. Open-weight, practitioner-tested local AI.
Compile with GPU backends for NVIDIA cards.
Cornerstone WikiWayne guide: llama.cpp Complete Guide. Open-weight, practitioner-tested local AI.
Leave the managed service when you need custom builds or flags.
Use the LM Studio catalog without guessing quant labels.
Cornerstone WikiWayne guide: LM Studio vs Ollama vs llama.cpp: Which Local AI Tool?. Open-weight, practitioner-tested local AI.
Cornerstone WikiWayne guide: Local AI Model Tracker (2026). Open-weight, practitioner-tested local AI.
Network egress, logging, and backup habits for homelabs.
Cornerstone WikiWayne guide: MLX on Apple Silicon for Local AI. Open-weight, practitioner-tested local AI.
Python venv, mlx-lm, and a tiny model smoke test.
CUDA maturity vs ROCm tradeoffs for GGUF stacks.
Point agents and UIs at `http://localhost:11434/v1`.
Cornerstone WikiWayne guide: Open WebUI for Local AI. Open-weight, practitioner-tested local AI.
Docker and bare-metal pairing for household chat.
From zero to a working chat with a small Ollama tag.
When to spend extra gigabytes on higher precision.
Cornerstone WikiWayne guide: Quantization Explained for Local AI. Open-weight, practitioner-tested local AI.
What runs at usable speed on 8 GB Pi hardware.
Cornerstone WikiWayne guide: Raspberry Pi Local AI: Limits and Use Cases. Open-weight, practitioner-tested local AI.
Cornerstone WikiWayne guide: Run Open-Weight Models Locally (2026). Open-weight, practitioner-tested local AI.
Cornerstone WikiWayne guide: VRAM Requirements for Local LLMs. Open-weight, practitioner-tested local AI.
GGUF packs tensors and metadata for llama.cpp-compatible runners.
Ollama favors CLI and API automation; LM Studio favors GUI model browsing. Compare setup, VRAM use, and GGUF workflows on real hardware.
A complete guide to self-hosting your own services in 2026 — from hardware and Docker to Nextcloud, Vaultwarden, and OpenClaw on a Raspberry Pi or VPS.