GPU OR NO GPU?

Do you need a GPU for a home server?

Usually not. File sync, Home Assistant, n8n, Paperless-ngx and many other services are happy without a dedicated graphics card. A GPU becomes useful when the workload specifically has something parallel or video-related to accelerate.

Jellyfin can benefit from video acceleration

If clients force the server to transcode video, supported integrated graphics or a dedicated GPU can make a huge difference. Modern integrated graphics can be more efficient than adding a large discrete card solely for media transcoding.

Local AI is the clearest GPU workload

LLM inference benefits heavily from GPU acceleration and available VRAM. Use the memory calculator rather than assuming any GPU is sufficient.

Most automation and storage services do not need one

A graphics card sitting mostly idle still consumes money, power and physical space. If the services do not use GPU acceleration, spend the budget on storage, backups or RAM instead.

Integrated graphics still count

“No dedicated GPU” does not mean “no acceleration”. Integrated media engines can handle useful video workloads without a separate card.