- Topaz Video AI produces the best AI upscaling results available in 2026 — if output quality is the only metric, it wins
- The $299/yr subscription is worth it for professional videographers and archivists who upscale frequently
- For occasional use, the processing time and $299/yr cost are hard to justify over faster alternatives
- GPU requirements are real — plan your hardware before purchasing
What we love (and don't)
// PROS
- Best-in-class upscaling quality for archival and restoration work
- Handles deinterlacing and motion interpolation better than competitors
- Multiple AI models for different use cases (upscaling, recovery, stabilization)
- Batch processing for large video libraries
// CONS
- $299/yr is a steep recurring cost for occasional users
- GPU-dependent — requires a recent Nvidia/AMD/Apple Silicon GPU; CPU processing is impractically slow
- Processing is slow even on good hardware — 4K upscaling runs slower than real-time on most systems
- Interface is functional but not polished compared to subscription-based competitors
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I’ve tested a lot of software that calls itself “AI-powered” and turns out to be a marketing label slapped on top of a Bicubic filter. Topaz Video AI is not that.
This is the real thing — a piece of software that does something genuinely difficult (reconstructing visual detail from low-resolution or degraded video using neural networks) and does it better than any competitor I’ve used. The question isn’t whether it works. It does. The question is whether it’s right for your situation, and that answer depends heavily on what hardware you’re running, how often you need it, and how long you’re willing to wait for renders.
I’ve been using Topaz Video AI for the better part of two years. I’ve run it through restoration projects on archival footage from the late 1990s and early 2000s, converted broadcast recordings from interlaced 480i to clean 1080p, and upscaled a few commercial projects where a client delivered footage at a lower resolution than agreed. Here’s the unvarnished assessment.
What Topaz Video AI Actually Does
Let’s be specific, because “AI video upscaling” gets used loosely.
Topaz Video AI has four core functions: upscaling (increasing resolution), enhancement (cleaning up compression artifacts and noise without necessarily changing resolution), frame interpolation (creating new frames between existing frames, useful for slow-motion or increasing frame rate), and deinterlacing (converting interlaced footage — those horizontal line artifacts you see on old TV recordings — to progressive scan).
Most competitors focus on one or two of these. Topaz handles all four, and critically, you can combine them in a single processing queue. Got old 480i footage you want at 4K and 60fps? Queue deinterlace, then upscale, then interpolate — it runs them sequentially as a single job. That pipeline capability is a meaningful practical advantage for archival work.
The software runs locally on your machine. Cloud Rendering is an optional extra service that sends files to Topaz’s servers; local rendering keeps your footage on your own machine (Source). For people working with sensitive content — corporate video, personal archives, client material — that matters.
The AI Models: Iris, Apollo, Proteus, and the Rest
Topaz’s models aren’t one-size-fits-all, which is both a strength and a source of confusion for new users.
Iris is the primary upscaling model. It’s optimized for footage with faces — people talking to cameras, interviews, documentary subjects. Iris is very good at reconstructing facial detail that compression or resolution limitations have destroyed. Put in a blurry, pixelated face and Iris will give you something that looks like it was shot at higher resolution. Not magic — it’s inferring detail, not recovering it — but the results are often remarkable. There are multiple Iris variants (Iris MQ, Iris LQ) tuned for different source quality levels.
Proteus is the model I use most for non-face content. It’s more of a general-purpose upscaler with manual control over parameters — you can adjust sharpening, detail recovery, noise reduction, and deblurring independently. More control than Iris, but requires more tuning. For landscape footage, architectural video, anything that isn’t primarily people, Proteus generally gives better results than Iris.
Apollo handles frame interpolation. This is the model that creates new frames between your existing frames — the mechanism for converting 24fps footage to 60fps or creating slow-motion from normal-speed footage. Apollo is genuinely impressive on stable footage with clear motion paths. But for the use cases it’s designed for, it’s the best interpolation I’ve tested outside of dedicated frame interpolation software.
There are additional models for stabilization and for specific deinterlacing tasks. The model library gets updated with each major Topaz release.
Choosing the right model matters. New users who just pick the first option and wonder why results are mediocre are usually using Iris on landscape footage or Proteus on faces. Topaz’s in-app guidance has improved, but there’s still a learning curve here.
GPU Requirements: The Part Marketing Doesn’t Emphasize
I’ll say this plainly: if you don’t have a capable GPU, Topaz Video AI is not a good purchase.
The minimum GPU I’d consider before buying this software is an Nvidia RTX 3060 or AMD RX 6700 XT on Windows. On Mac, anything M1 or newer is good — Apple Silicon’s Neural Engine handles Topaz’s workloads well, and the M2/M3/M4 chips are genuinely fast with it.
There’s also VRAM to consider. 8GB VRAM handles most 4K upscaling jobs. For most users, an 8GB card is fine.
What I tell anyone evaluating this software: check your GPU specs before purchasing.
Processing Speed: The Honest Numbers
Nothing processes faster than real-time on most hardware. Plan accordingly. For batch work on large libraries, Topaz supports queue-based processing — you set up all your jobs, start the queue, and leave it running overnight. That’s how I actually use it for large projects.
Batch processing is one of the software’s underrated practical features. Set up 20 jobs, queue them in order, go to bed. Wake up to processed files. For archival work where you’re converting an entire library, this is the only sane workflow.
Output Quality: Where Topaz Earns Its Price
Here’s the part where I sound like a fanboy, and I’m fine with that because it’s accurate.
The quality difference between Topaz’s output and most competitors is visible. Not “squint at it and maybe” visible — obviously, clearly visible on a decent monitor.
I took a set of clips from a 2001 home video recording — VHS-to-digital transfer, 480i, significant compression artifacts, some motion blur — and ran them through Topaz, DaVinci Resolve’s Super Scale, and two subscription-based online upscaling services. The comparison was not close. Topaz produced footage where faces were readable and backgrounds had coherent detail. The others produced footage that was higher resolution but preserved the blurriness of the original — just bigger blur.
That’s the key insight about AI upscaling quality: adding resolution isn’t the hard part. Recovering or reconstructing believable detail is what separates the good tools from the mediocre ones. Topaz’s models are trained on an enormous variety of footage types, and it shows in edge cases — heavily compressed web video, old broadcast recordings, poorly shot archival footage. That’s where the difference is most apparent.
For clean, well-shot modern footage going from 1080p to 4K, the gap between Topaz and competitors narrows. DaVinci Resolve’s Super Scale does a respectable job on clean material, and it’s free with Resolve Studio. If all you’re doing is polishing already-good footage, Topaz’s $299/yr price against free alternatives starts to look less compelling.
Where Topaz has no real competition: degraded, compressed, or archival material. If that’s your use case, there’s no other tool I’d recommend.
Related: if you’re working with still images, Topaz Labs makes Topaz Photo AI — a separate product with overlapping DNA. The upscaling models are related, but Video AI’s temporal processing (using information from surrounding frames to inform reconstruction) is what makes the video product distinctly better than applying photo upscaling frame by frame.
The Interface: Functional, Not Fun
I’m not going to pretend the interface is great.
It works. You import a clip, choose your models, preview a frame or short segment, adjust settings, and export. The preview system — which shows you a before/after comparison before committing to a full render — is actually well-designed and prevents a lot of wasted processing time. The settings panel is logically organized.
But compared to something like Runway ML’s interface — which is polished, modern, and clearly designed with UX in mind — Topaz feels like software designed by engineers for engineers. Dense, utilitarian, somewhat unforgiving of new users.
The preset system has gotten better. There are now useful default settings for common tasks that give new users a reasonable starting point. But you’ll still want to watch a few tutorials before diving into anything complex.
Documentation has improved in recent versions. The in-app tooltips are more descriptive than they used to be. Still not a product where you open it and immediately know what to do, but it’s no longer as opaque as the v3.x era.
Pricing: Is the $299/yr Subscription Worth It?
Topaz Video is sold as a subscription: $299/yr on the individual annual plan (Source).
Is it worth it? Depends entirely on use frequency and use case.
Worth it if: You’re a professional videographer or filmmaker who regularly upscales client footage. You’re an archivist or restoration specialist. You’re converting a substantial personal library of old footage. You have an RTX 3070 or better (or Apple M1+) and can handle the processing time. You do this work more than a few times per year.
Not worth it if: You need to upscale one video occasionally. Your GPU is below Topaz’s recommended RTX 30 series or Radeon 5000 series floor, or pre-M1 Apple Silicon (Source). You need fast turnaround and processing speed matters more than quality. Your source material is already clean, modern footage where cheaper tools perform adequately.
Topaz is genuinely iterative on model quality — the models in the current version are meaningfully better than what shipped two years ago.
How It Compares to the Competition
DaVinci Resolve Super Scale: Free with Resolve Studio. Good on clean footage. Not competitive on degraded or heavily compressed source material. No frame interpolation comparable to Apollo. For anyone already working in Resolve, Super Scale is worth trying before paying for Topaz — you might find it sufficient.
Neat Video: Primarily a noise reduction plugin — doesn’t do upscaling. Excellent at what it does. Complementary to Topaz, not competitive with it.
Runway ML and online AI video tools: Subscription-based, cloud-processed. Much faster turnaround for short clips. Significantly worse output quality on challenging material. Better interface. For creators who need quick enhancement of web-quality content, these tools are faster. For anyone who cares about maximum quality, they don’t compete.
AVCLabs Video Enhancer AI: Lower price point, similar capability claims. I’ve tested it. The upscaling quality on degraded material is noticeably inferior to Topaz’s. The interface is cleaner. For budgeted work where Topaz’s quality ceiling isn’t required, it’s a consideration. For serious archival work, it’s not in the same category.
Nothing currently competes with Topaz on output quality for difficult source material. That’s a claim I make with reasonable confidence after testing everything I could find.
Who Should Buy Topaz Video AI
Buy it if you’re a videographer, filmmaker, or archivist who regularly works with footage that needs quality enhancement — upscaling old material, recovering detail from compressed video, deinterlacing broadcast recordings. The output quality is the best available, the $299/yr pricing is fair for professional use, and the batch processing capability makes large-library work tractable.
Don’t buy it if you’re an occasional user who occasionally wants to clean up a single video clip. The $299/yr cost doesn’t make sense for that use pattern, and the processing time will frustrate you on anything less than a current-generation GPU.
Topaz Video does not offer a free trial for the current desktop version; Topaz Labs support points evaluators to the legacy Video AI builds instead (Source).
Rating: 8.6/10. Loses points for interface polish, GPU requirements that many users won’t meet, and processing speeds that remain slower than I’d like even on good hardware. Earns the score for output quality that genuinely has no equal at any price point in 2026.