- Choose your setup based on real work, not isolated benchmarks.
- Understand why Windows/WSL2 fails more often with GPU and Docker.
- See where Mac Apple Silicon shines and where it falls short.
Quick decision
- Mac M-series: simplicity, battery life, quiet operation, MLX, easy Ollama, good dev environment.
- Windows + NVIDIA + WSL2: more compatibility with enterprise tools and powerful GPUs, but more failure points.
- Linux bare metal: best for servers, vLLM, Docker GPU, and serious homelab.
# Windows: primer diagnóstico wsl --status wsl --list --verbose nvidia-smi docker run --rm --gpus all nvidia/cuda:12.5.0-base-ubuntu22.04 nvidia-smi # Mac: primer diagnóstico sw_vers ollama --version ollama ps
Common errors by platform
- Windows/WSL2: GPU not detected, Docker without GPU access, duplicate drivers inside WSL, CUDA permissions, odd ports.
- Mac: long context that spikes memory, slow prefill on huge prompts, unified memory limits, and less support for CUDA stacks.
- Linux: drivers, CUDA toolkit, container versions, and updates that break builds if you don't pin versions.
Official sources
- NVIDIA CUDA on WSL User Guide
- Microsoft: Enable NVIDIA CUDA on WSL 2
- MLX documentation