Buying a new graphics card (GPU) can be difficult, especially if it involves all the technical issues you’re not familiar with.

Most consumers in the graphics card market just need to understand the performance of the graphics card in their favorite game and make a purchase decision. But if you want to buy a GPU for video editing or 3D rendering, it’s much harder to find that information.

Especially with 3D rendering, you can save a lot of time and money if you render as quickly as possible.

How to distinguish a rendering GPU from an editing GPU?

Especially if you’re not familiar with graphics technology, you have a lot of questions to answer.

We’re going to assume basic familiarity here, that is, you know that gpus stand for graphics processing units and graphics cards are expansion cards that contain one or more Gpus.

Image credit: Nvidia

What’s the difference? Professional Gpus vs. consumer Gpus

Today, consumer and professional Gpus look more similar than ever.

Some Gpus even blur the lines slightly, such as AMD’s Radeon VII or Nvidia’s Titan series.

After all, these cards come with an extremely high price tag and an illusory amount of VRAM.

Today, let’s take a look at the Nvidia RTX GPU. What is the difference between a consumer-oriented GeForce RTX card and a professional Quadro RTX card?

Credit: PNY

They all use the same hardware architecture and can sometimes even be specified to handle kernels and VRAM, but Quadro is several times more expensive… Is it just a scam?

Let’s take a look:

Professional GPU

The biggest difference between consumer gpus and professional Gpus is software.

Nvidia’s Quadro card and AMD’s FirePro card are optimized for high-end productivity applications with extremely thorough compatibility with industry-leading applications.

In addition, they are supported for many years and are viewed as long-term investments, whereas consumer graphics cards are not.

Pro Gpus have been tested with industry applications and drivers have been optimized for maximum performance. Many advanced industry applications (such as the popular CAD application Solidworks) have special features (such as RealView in Solidworks) that are only supported if you have a professional GPU.

For example, the following figure shows the Nvidia Gpus officially supported by Solidworks:

Image credit: Solidworks

If you are using a professional GPU, some software vendors will only support you and provide after-sales maintenance.

This is critical for large companies, where uptime on a server or workstation is critical to keeping their expensive employees working on functional PCS at all times.

It does make sense. Companies with enough money to buy Quadro Gpus. Software developers support companies with adequate funding. These companies also usually have dedicated IT staff with sufficient expertise.

How to make less trouble and more effective:

1. Solidworks support personnel talk to the company’s IT specialists and can then resolve some Solidworks glitches on all the company’s PCS

2. Many Solidworks support people talk to hundreds of individual users who don’t understand PC/Tech/IT

When you purchase a Pro-GPU, you purchase pro-Support. (Except for some hardware features)

Consumer GPU

Consumer Gpus will be great for games and consumer applications.

They can also be very good at photo and video editing, whereas powerful consumer Gpus (such as the Nvidia RTX 2080Ti) are often overrated.

Consumer Gpus are also great for GPU rendering because GPU rendering engines typically don’t have features that can only run on professional Gpus.

Professional Gpus, however, usually… Not very good at games, but superb at editing, rendering and almost any other professional-level task, however, for the same performance, professional Gpus will be more expensive.

So if you know that the software you choose doesn’t use features that require a professional GPU, and you don’t need a lot of VRAM in a professional GPU, then a consumer GPU is almost always a better choice, especially in terms of cost performance.

But let’s dig into some details.

CUDA cores, or why Nvidia is favored here

CUDA cores refer to special processing cores found in Nvidia Gpus that are proprietary to Nvidia.

CUDA stands for Compute Unified Device Architecture, and these cores inside Nvidia Gpus essentially act as raw computing power, not raw graphics power.

This is why they are used to enhance computation-intensive effects in supported captions (such as Nvidia HairWorks), and gpus alone are not enough to do the job.

For editing and rendering, CUDA cores are an essential source of additional computing power needed to perform a given task.

Most editing and rendering applications are optimized in some way to take advantage of the CUDA kernel, so adding more features to your system will enable you to render models, videos, and so on better and faster.

Some popular GPU rendering engines (such as Octane and Redshift) are built based on Nvidia’s CUDA, which means you have to have an Nvidia GPU to use them. In such rendering engines, rendering performance is almost linearly proportional to the number of CUDA Cores the GPU has.

Certain applications (such as Adobe’s After Effects or Premiere Pro) bring support for both Nvidia and AMD Gpus, but generally run faster on Nvidia Gpus.

GeForce or Quadro?

GeForce will bring you the most value when it comes to things like editing video and raw 3D application performance.

However, because GeForce is a brand primarily aimed at gamers and consumers in general, high-end professionals may need to lack some features.

Quadro can provide high performance in many applications, but the main attraction is its software support for enterprise users.

Any performance gained comes at a high price compared to GeForce.

However, if you need ECC (Error-correcting code Memory) or the best driver that is absolutely suitable for professional applications, then Quadro is the best choice ~

GeForce is focused on gaming and consumers, while Quadro is focused on enterprise and enterprise users.

In addition, Quadro will have a higher CUDA kernel and VRAM count, and will sometimes have unique features such as ECC, which we’ll discuss later.

In general, we recommend Quadro to:

  • High prices can be written off as business expenses

  • Can take advantage of ECC, larger VRAM, higher floating-point accuracy, higher monitor bit depth

  • Special software features that require only professional GPU support (e.g. Solidworks, Autocad…)

  • Rely on software vendors for maintenance and support on a regular basis

  • Its hardware needs to be thoroughly tested to ensure its durability and stability in an enterprise or server environment, even at 24/7 uptime

We recommend GeForce to:

  • Don’t take advantage of features supported only by Pro-level Gpus

  • Want more money to make money

  • You don’t necessarily need a lot of VRAM or ECC

  • Don’t rely on regular software support from their application vendors

  • You might want to play a game from time to time

Do I need RTX?

Nvidia’s “Turing” architecture was the first to introduce RTX, and it brought some functionality on top of the CUDA kernel (RT and Tensor kernel).

Image credit: Nvidia

The RT kernel is for ray tracing and was built specifically for it.

For professional rendering, at least in supported applications, having a more powerful ray-tracking GPU can greatly speed up the workload.

If you don’t need a ray-tracking GPU (especially if you focus on video editing rather than 3D rendering), then the RT kernel doesn’t make a big difference.

At the heart of Tensor is another story that gets even more interesting.

In consumer Gpus, the Tensor core is used to implement features such as DLSS (deep learning supersampling), which uses AI to improve image quality.

For professional use, the Tensor kernel takes advantage of its powerful FP16 / FP32 and INT4/8 capabilities, making it ideal for neural networks, deep learning, artificial intelligence, and more.

If these areas sound like something your enterprise wants to explore, then Quadro RTX may be just the thing for you.

RT Core also dramatically improves rendering speed, at least in the supported rendering engines. For example, Octane and Redshift are working on implementations using RayTracing Cores.

All in all, the RT and Tensor kernel add some nice extra features that may or may not make a difference to your workload.

However, we still recommend replacing RTX Gpus with previous generation Nvidia Gpus, as the latest RTX Gpus do offer significant performance improvements over non-RTX predecessors, even without taking advantage of these additional processing cores.

What does it take to edit a GPU?

Video editing requires far less GPU demand than professional rendering.

Even your Nvidia base consumer GPU with a CUDA core can get the job done here, especially if you’re just a content creator freelancing or Posting to sites like YouTube.

Check out the following Premiere Pro video editing benchmarks to clearly show where the GPU Sweet Spot is:

Video and photo editing doesn’t require any imagination and doesn’t require the over-the-top Quadro GPU specs and price tag, so you’ll be a good fit for a low-end or mid-range GeForce RTX GPU.

If your needs are more enterprise-class (i.e. 4K / 8K HDR video), then you may want to opt for a high-end GeForce RTX GPU.

What do you need a rendering GPU to do?

From the rendering GPU (explicit 3D rendering in a professional environment), you will need more help from the GPU.

The biggest thing you need for a rendering GPU (given that it’s compatible with the rendering engine you’re using) is as many CUDA cores and VRAM as possible.

The time it takes to render an average frame on a GPU is almost linearly inversely proportional to the number of CUDA cores the GPU has.

However, if the 3D scene data fits its VRAM (video memory on the GPU), the GPU can only take advantage of its huge CUDA Core capabilities.

This means that if you know a scene with millions of polygons, sub-polygon shifts, or very complex scenes such as large textures, the VRAM requirements will be much higher than if the scene is fairly simple with just a few objects.

Most GeForce RTX Gpus already have a fair amount of VRAM, usually between 8GB and 11GB, but if you need more, you must use a Quadro RTX GPU, which has up to 48GB of VRAM.

In a Quadro GPU, you’ll also get ECC, which we’ll explain now.

ECC: What is it and why do you need it

ECC stands for error-correcting code memory.

ECC memory detects and corrects data errors that naturally occur during long periods of high workload.

These errors are the cause of seemingly random events, such as data corruption or system failures, and must be avoided at all costs when dealing with sufficiently fragile data.

This is why ECC is most commonly used in servers and enterprise PCS – to prevent these errors from occurring when they cause the most damage.

Among Gpus, ECC is unique to Nvidia and AMD’s specialized Gpus.

In the case of Nvidia, these are only present in Nvidia Quadro Gpus and are necessary to prevent fatal errors in some cases.

However, most consumers and creators who are not integrated into enterprise workflows can safely ignore ECC.

Assess performance

The first and best way to evaluate the performance of a given GPU is to look at the baseline.

Typically, consumers look at benchmarks for games and other applications to best understand the performance of a given component.

In general, the same idea applies here, but you do need to know which benchmarks to focus on.

For GPU rendering, you have benchmarks for popular GPU rendering engines such as OctaneBench, Redshift, and VrAY-RT.

Other resources may also be helpful, including Passmark’s GPU computing baseline table, which measures DirectCompute/OpenCL performance.

In addition to benchmarks, there are core specifications, which we will list in each selection below.

The core specs we are dealing with are:

  • CUDA core — corresponding to raw processing power (a huge indicator of 3D rendering performance)

  • Tensor core — corresponding to deep learning/AI features and fp32/16 workloads

  • RT core – Can be used as an accelerator for 3D rendering in supported rendering engines, corresponding to ray tracing capabilities

  • VRAM – Used for managing large scenes, editing, etc., without taking up too much memory

  • GPU frequency — A measure of GPU core speed

Top GeForce and top RTX GPU specifications table

Note: Actual prices may vary. Quadro RTX cards are often much cheaper than MSRP, while non-Quadro cards are often higher or lower than MSRP.

As you can see from the table, the biggest hardware differences boil down to the vastly improved VRAM (with ECC) and the significantly improved CUDA, Tensor and RT cores, at least at the high end.

In addition to including the ECC, the Titan RTX also offers similar specifications to the high-end Quadro RTX card.

Key points:

The main reason Quadro was chosen over GeForce was for increased stability and driver support for enterprise-class software — otherwise, the GeForce card could have achieved similar performance at a lower price in many cases.

Should I use a dual GPU?

If you’re building a game system, our answer is simple: No, absolutely not.

On the gaming side, multi-GPU support has been greatly reduced and is not recommended.

But to increase productivity… Well, that’s a different story.

Games need to leverage standards like SLI to render a scene with multiple Gpus, and most editing and rendering applications are done with distributed workloads in mind.

This means that not only can you have two cards without the GPU working perfectly in coordination, but you can also see a linear 2x performance increase, allowing you to add another GPU to your workload!

Dual Gpus are not high-end products. As more cards are added to compatible systems, the performance of workloads (such as 3D-GPU rendering) increases almost linearly, and for 3D-Artists, HEDT PCS with up to 4 Gpus are common.

A quick note on Nvidia’s NVLINK:

However, to take advantage of NVLINK memory sharing, you will need a higher-level GPU than the RTX 2070 Super. In addition, memory cannot be shared between more than two Gpus at a time with NVLINK, and rendering engine support is required to use these features.

You will need an NVLINK bridge to connect two cards.

Dual/multi-GPU setup for video editing in Adobe Premiere Pro?

Premiere Pro doesn’t use multiple Gpus on your system, so you won’t benefit from multiple Gpus.

Best editing and rendering graphics card: Ruiyun’s recommended choice

1. Best value editing and rendering GPU: Nvidia RTX 2060 Super

Parameters:

  • CUDA core – 2176

  • Tensor Cores – 272

  • RT kernel – 34

  • VRAM GDDR6-8 gb

  • GPU frequency — 1470 MHz (basic)

If you are on a budget but still want good performance when spending money on editing and rendering tasks, the RTX 2060 Super is our top choice.

It offers overall superior performance for gaming and professional work compared to other Gpus in its price range. (For gaming, though, the AMD RX 5700 is definitely a better choice.)

RTX 2060 Super has just the right amount of RT and Tensor cores and a decent amount of CUDA cores to edit 1080p and 1440p videos.

In OctaneBench, the card scored about 205, which is much better than the Quadro RTX 3000 (149) and Quadro RTX 5000 (184).

That means the raw computing power available to the 2060 Super exceeds even that of a Quadro RTX card that costs several times more, which is not bad.

These results place the RTX 2060 Super firmly in the middle of the pack for computing performance on a single GPU card.

For those just getting started with editing and rendering, or without thousands of dollars of hardware investment, the RX 2060 Super is an ideal place to start.

Need a dual GPU? It was replaced by the blower-style RTX 2060 Super

2. Best high-end editing and rendering GPU: Nvidia RTX 3090

Parameters:

  • CUDA core – 10496

  • Tensor Cores – 328

  • RT core – 82

  • VRAM – 24 gb GDDR6X 9

  • GPU frequency — 1400 MHz (basic)

If you’re on a tight budget, don’t need AN ECC, and don’t want to sell a kidney to buy a graphics card, get the Nvidia RTX 3090.

For gaming purposes, the RTX 3090 doesn’t really improve performance per dollar compared to its low-end counterparts.

However, it does offer a significant improvement in raw computing performance compared to its non-TI counterparts above, making it a more attractive option for “editing and rendering”.

The RTX 3090 scores 661 on OctaneBench, making it firmly in the top tier of single-GPU cards in terms of single-GPU performance.

All of these factors make the RTX 3090 the preferred choice for this class. If you’re handling 1440p / 4K video or regular demanding rendering tasks, the 3090 is one of the best graphics cards for that job.

3. Best high-end professional GPU: Nvidia Quadro RTX 6000

Parameters:

  • CUDA core – 4608

  • Tensor Cores – 575

  • RT core – 72

  • VRAM — 24 GB GDDR6 (ECC)

  • GPU frequency — 1440 MHz (basic)

Last but not least, let’s take a look at Quadros.

In terms of raw performance, the Quadro RTX 6000 is no better than the RTX 2080 Ti outside of vRAM-constrained scenarios.

This was reflected in OctaneBench, which showed a 302 of 2080 Ti of just 308 inches — an incredible margin difference. However, if you’ve read the article, you’ve probably figured that out.

The main motivation for obtaining a Quadro RTX card was enhanced software support, stability and ECC RAM support.

If you want something in this cost-effective range, but the Quadro RTX 6000 does not offer what you need, consider the following three options.

If the card looks a bit VRAM constrained, choose the Quadro RTX8000. Most of the specs are the same, but the VRAM is doubled.

Performance differences in non-VRAM binding scenarios are very limited.

If ECC is inessential to your workload, then you can also be much cheaper and get an Nvidia Titan RTX with nearly the same specifications.

If ECC doesn’t matter, your workload and you don’t mind overpaying around the same price, also consider the Titan V.

It doesn’t have an RT kernel, but it does have enough computing power — the best of any single GPU, according to OctaneBench — and it still has more Tensor and CUDA cores to work with. It does, however, have less VRAM.

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