We have released an update to NNSuperResolution, v4.1.0. This is more of a maintenance release, which means that the upscaling models included are the same as in v4.0.0. That said, it does feature some good internal optimizations for making the VRAM usage more stable (i.e. with less spikes of increased VRAM needs). We’ve also added the possibility to automatically process using the GPU index that was specified on the Nuke batch render command line (using the –gpu parameter). Nuke16.1 and Nuke17.0 are now supported as well on all platforms.
Next up for us is to do a similar overhaul of NNCleanup. And of course continue work on our next plugin, exciting times!
We are incredibly excited to share the biggest update yet to our optical flow plugin. This release brings massive improvements to vector generation and introduces a brand-new warping workflow directly into your Nuke scripts.
What’s new in v3.0:
The “AAA” Model: Our new model variant generates highly detailed, exceptionally smooth, and less noisy vectors, while being much better at handling larger input resolutions.
Introducing NNFlowVectorWarp: This new node is a direct, tailor-made alternative to NukeX’s VectorDistort. Optimized specifically for our NNFlowVector vectors, it allows you to seamlessly track patches, stabilize live-action footage, and output STMaps for heavily optimized pre-rendered pipelines.
Updated Nuke Compatibility: We now fully support the latest Nuke releases (Nuke 16.1 and Nuke 17.0) across Linux, Windows, and macOS.
Smarter Farm Rendering: Batch rendering on multi-GPU setups is now completely seamless, as the plugin automatically respects the –gpu parameter in your Nuke batch render commands.
And as always, if you already have a license, just go ahead and update to the new version. We never restrict our licenses to specific versions of our plugins.
If you haven’t got a license yet and you are keen to give this a try, please request a free trial license using this page: Request trial license
We are happy to announce that we are doing a Black Week sale this year as well!
Use the following discount codes at checkout, depending on what type of licenses you are ordering. The discount will be applied directly before you pay:
blackweeksingle – 35% off the license types “node locked”, “floating” and “render”.
blackweeksite – 15% off the “site license” type.
blackweekglobal – 10% off the “global license” type.
The discounts are only valid this week, i.e. until the last of November (30th of November, 2025).
This is probably your best chance to buy at the current lowest prices for the foreseeable future, as we’ll be raising prices in January 2026, as previously announced.
It’s been five years since Pixelmania opened shop and, in that time, inflation has climbed while exchange rates have swung wildly. To keep investing in new features and fast support, we’re refreshing our licence prices and rolling out local-currency billing so you can pay in the money you use every day.
License
Today
From 1 January 2026 (USD)
Node-locked
$99
$119
Floating
$129
$159
Floating render-only
$59
$69
Site license
$1950
$2350
Global license
$9500
$11500
New currencies at checkout
When you visit the store you’ll now see prices in your own currency—automatically converted at the live FX rate and rounded to sensible numbers. Newly supported currencies are:
🇦🇺 Australian dollar (AUD)
🇨🇦 Canadian dollar (CAD)
🇪🇺 Euro (EUR)
🇬🇧 Pound sterling (GBP)
🇮🇳 Indian rupee (INR)
🇯🇵 Japanese yen (JPY)
(A drop down switcher beside the search bar, top right corner, lets you flip currencies manually if you prefer.)
Key points
Six-month grace period – All purchases and renewals made up to 31 December 2025 lock in the current price for the full year of the licence.
Same licences, same terms – Only the numbers change; licence types, features and support remain exactly as you know them.
Why now? – US consumer prices have risen ~25 % since 2020 and the USD/SEK rate has moved ~15 % this year. The update restores the real value of a licence so we can keep shipping reliable, well-supported tools.
Timeline
1 July 2025 (today) – This announcement + multi-currency checkout goes live.
Until 31 Dec 2025 – Buy or renew at current prices.
1 Jan 2026 – New pricing takes effect.
If you have any questions please write to [email protected] – we’re happy to help.
We have just released NNSuperResolution, NNFlowVector and NNCleanup with support for Nuke15.2 and Nuke16.0 on Linux, Windows and macOS. Please head over to the downloads section to get your copies.
General Pixelmania update: We are currently putting a lot of developer time into a sequence mode for NNCleanup. This is a tricky one that will take a good amount of time before it’s ready for a public release. But we figured it’s nice for you to know what we are up to!
We are happy to announce that we are doing our first Black Week sale ever! Please use the following discount codes in the checkout process, based on what type of licenses you are ordering, and the discount will be applied directly before you pay:
blackweeksingle – This will give you 35% off on the license types “node locked”, “floating” and “render”.
blackweeksite – This will give you 15% off on the license type “site license”.
blackweekglobal – This will give you 10% off on the license type “global license”.
The discounts are only valid this work week, i.e. until the last of November (30th of November, 2024).
We are happy to finally be able to release NNSuperResolution v4.0.0! This new major release features fully retrained networks for all upscale solutions (stills as well as for sequences). The biggest difference is that we have replaced the previously rather simplistic optical flow module with the very successful and much more performant variant “A” model from NNFlowVector. We have also increased the dataset size and the training resolution. These tweaks together makes the new models perform better overall in terms of sharpness and with less alignment artifacts. We are also adding support for Nuke15.1 (like with the recent update releases of NNCleanup and NNFlowVector).
Have a look below to see a comparison between NNSuperResolution v4.0 and v3.4. We showcase three example frames from three different videos upscaled 4x in sequence mode:
NNSR v3.4
NNSR v4.0
Source
NNSR v3.4
NNSR v4.0
Source
NNSR v3.4
NNSR v4.0
Source
We did investigate and train different solutions for upscaling stills with alpha channel support. Unfortunately none of them were good enough to release at this point, so we decided to release all the other significant updates anyway to not hold on them for too long. Hopefully this is something we can revisit in another upcoming release, but for now it has been put lower on the prio list again.
It’s great to finally be able to release this version as it has been in the making for almost a full year by now (it has been A LOT of model training). We hope you like it!
We have recently released new point release versions of NNFlowVector and NNCleanup. One important feature for both of these releases is the support for Nuke15.1, which is the latest Nuke release from Foundry that was made public in June earlier this year. Nuke15.1 has updated the bundled version of PyTorch from v1.12.1 to v2.1.1, which is a rather huge step in development for PyTorch. This means faster and better execution for machine learning models in general, but the biggest difference is for the MacOS platform. The old version (PyTorch v1.12.1) was the first that supported MPS acceleration, but there was quite a lot of instructions that wasn’t ready and automatically was executed on the CPU instead. With the new release (PyTorch v2.1.1) the MPS support is way more mature and the speed has improved significantly. Here is a speed test we ran for NNFlowVector on a Full HD clip (and process scale set to 0.5) on a MacBook M3 Pro, 36Gb unified RAM:
As you can see above, the speed has more than doubled between the Nuke15.0 build and the Nuke15.1 build (using the same version of NNFlowVector, v2.3.0).
NNFlowVector v.2.3.0 also features a new transformer variant called “BB”. This variant is similar to the “AA” variant, but it has been trained on larger image areas (using a much larger GPU) which makes it perform even better in most scenarios. Our recommendation is to at least try the default “A” model variant, and also the “AA” and “BB” variants when testing which variant is best for your specific material. NNFlowVector v2.3.0 also features an important fix for anamorphic material.
NNCleanup v1.5.0 also features a whole new suite of model variants, called “AAA“, “BBB“, “CCC” and “DDD“. These have been trained using a much larger batch size on a much larger dataset, which makes them perform quite a lot better in general. (Because of this, we have deprecated the original “A”, “B”, “C” and “D” model variants.).
We hope you find these updates as useful as we do! Cheers, David
The latest release of Nuke changed a lot when it comes to being able to support the macOS system from our side. Since Nuke15.0 is natively compiled for the arm64 architecture, i.e. Apple’s M processors/silicon, and comes with PyTorch 1.12 internally bundled which supports being accelerated using MPS (Apple’s Metal Performance Shaders) it is suddenly possible for us to build compatible and accelerated plugins.
This is what we have primarily spent the last couple of months doing, i.e. building, adapting and testing NNSuperResolution, NNFlowVector and NNCleanup for Nuke15.0 on macOS. They all work well and we feel they are ready for a public release, which is very exciting!
However, it’s worth noting that the MPS support in PyTorch 1.12 is still very early, and hence the support is not fully fleshed out. This means that the MPS acceleration performs well is some situation and not so well in others. It works better for NNSuperResolution than for NNFlowVector as an example. This is however just a matter of time until it’s improved, because as soon as Foundry decides to update the internal PyTorch version that is shipped with Nuke, there will automatically be much better and updated support for MPS in general. Hopefully we will already benefit from this in Nuke15.1, time will tell.
Having noted the above, the only real difference that you will notice as an artist while using the plugins is that NNFlowVector on macOS will not accelerate the “AA” transformer based model for now (it will automatically switch to classic CPU processing so it will work, but just be very slow). Otherwise than that, it should all be very familiar to the use on Linux/Windows.
As a final note, to be super clear, you need to have an Apple M processor machine to be able to use these new macOS builds of the plugins (they will NOT work on older Intel based macs).
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