Deadline Distributed Batch

This is the exact same node as DistributedBatch wearing a Deadline-branded name, so the short version is: see that node's article for everything that matters. One default_batch input (1–64, default 1), one batch_size integer output. On a worker it multiplies your default by the injected worker batch multiplier; on the master it multiplies by the master.batch_size setting in gpu_config.json. Wire the output into your Empty Latent's batch slot and each GPU in the farm renders the right number of images.

Why does this duplicate exist at all? Because the pack ships "Deadline-named node aliases for cleaner Deadline workflows," as the README puts it. When you're building a Deadline submission, the job metadata and the workflow that a Deadline task actually runs can be written with names that make it obvious you're on the Deadline path. The aliases aren't different code - they map to the same classes - so either name behaves identically. Pick one and stay consistent; a workflow saved with one name will load fine either way.

The only real gotcha here is the same one that bites everyone: default_batch is a per-worker baseline, not the total you want rendered. Five workers with a default of 4 gives you 20 images, not 4. If your output count surprises you, check gpu_config.json for the master multiplier and your worker config for the worker one.

If you're not running a Deadline farm, you don't need this name. DistributedBatch is the cleaner choice for a hand-configured master/worker setup. The Deadline-prefixed versions exist for the studio path - thinkbox Deadline jobs, deadlinecommand, the whole VFX render-manager ecosystem - where keeping node names aligned with the Deadline vocabulary saves a lot of confusion in the submission UI.