Stations de travail pour Nuke – neuves et reconditionnées

FAQ

What kind of workstation works well for Nuke?

Nuke puts heavy demands on the CPU, RAM and storage, and some features also use the GPU. For 2D compositing, what matters most is a powerful multi-core processor, plenty of RAM and a fast NVMe SSD. For 3D, Deep or machine learning-based tools, a graphics card with enough VRAM becomes more important. It's best to match the configuration to your typical projects, such as footage resolution and number of layers.

How much RAM do I need for Nuke?

As a rough guide, 32 GB is enough for simpler HD projects. For 4K footage, many layers and a large cache, 64 GB or more is more comfortable. Too little RAM forces Nuke to write to disk and slows down playback. If you work on heavy scripts, choose a configuration that allows you to expand the memory later.

Do I need a powerful graphics card for Nuke?

It depends on the tasks. Standard compositing relies mainly on the CPU, but the GPU speeds up certain nodes, such as machine learning ones (CopyCat), as well as viewer playback and 3D work. Choose a card with certified drivers and enough VRAM. Check the current requirements in the Nuke manufacturer's documentation for the version you use.

Is a used ex-lease computer worth buying for compositing in Nuke?

Yes, as long as its specs suit your projects. Used workstations from reputable manufacturers, coming off lease, usually have plenty of cores and support large amounts of RAM. They are also solidly built and cost less than new models. Before buying, check the processor generation, graphics card, upgrade options and warranty terms.

What should I consider when choosing a drive for Nuke?

A fast NVMe SSD works best for the operating system, applications and current projects. A separate drive for the cache and frame sequences takes the load off the main drive and speeds up playback. For archiving finished projects, a larger, cheaper drive is enough. Choose the capacity based on the size of your footage, as high-resolution sequences quickly take up space.