Optimises deep data by reducing sample counts via occlusion culling, contribution thresholding, volumetric collapse, and colour-aware Z-merging.
DeepThinner v2.0
First submitted: 25 February 2026
Updated: 26 February 2026
Author: Marty Blumen
Website: https://www.martyblumen.com/
Compatible Nuke versions: 16.0 or later
Compatibility: Windows
DeepThinner v2.0 - Deep Sample Optimisation for Nuke 16
DeepThinner reduces deep sample counts to improve performance, reduce memory usage, and shrink deep EXR file sizes, often by 50 to 90 percent, with no visible quality loss.
Deep renders commonly contain redundant transparent, volumetric, or fully occluded samples. DeepThinner removes this unnecessary data using fast, artist-controlled optimisation passes.
Key Features
• Removes occluded and non-contributing samples
• Compresses dense volumetric micro-samples
• Merges visually identical neighbouring samples
• Optional per-pixel sample cap for memory control
• Live statistics showing reduction percentage
• Preserves all channels and AOVs
• Thread-safe and production-ready
Optimisation Controls
Depth Range, Alpha Cull, Occlusion Cutoff, Contribution Cull, Volumetric Collapse, Smart Merge, and Max Samples can be used independently or combined.
Typical Results (predicted)
60 to 85 percent reduction in character and volumetric shots
40 to 70 percent in atmospheric renders
30 to 60 percent in complex deep comps
Usage
Place DeepThinner before DeepMerge, DeepHoldout, or DeepWrite.
Default settings provide safe, effective optimisation for most shots.
Requirements
Nuke 16.0v1 or later
Windows
Installation
Copy the plugin and menu.py to your .nuke directory or any location on your NUKE_PATH.
Node location: Deep > DeepThinner
import nuke
toolbar = nuke.menu("Nodes")
deepMenu = toolbar.findItem("Deep")
if deepMenu is None:
deepMenu = toolbar.addMenu("Deep", icon="DeepToolset.png")
deepMenu.addCommand("DeepThinner", "nuke.createNode('DeepThinner')", icon="DeepThinner.png")
Build from Source
https://github.com/bratgot/DeepThinner
Version History
v2.0 - Major update with seven optimisation passes, volumetric collapse, colour-aware merging, and live statistics
v1.0 - Initial release
MIT License
Copyright (c) 2026 Marten Blumen
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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