If you are shopping for a new GPU you might have noticed the number of CUDA cores/stream processors in an AMD/NVIDIA GPU.
What is the difference between the two and why are they in such large numbers?
Here’s what you need to know about NVIDIA CUDA cores Vs AMD Stream processors. What makes them so special, is the impact they have on GPUs and which one is more powerful.
NVIDIA CUDA Cores vs AMD Stream Processors
Just like CPUs have their cores GPUs also have their own cores. AMD calls their cores stream processors and NVIDIA calls their CUDA (Compute Unified Device Architecture) cores. These GPU cores are also known as pixel processors or pixel pipelines.
Just like CPU cores, the more NVIDIA CUDA cores or AMD stream processors a GPU the more powerful it is.
That means if you have two different GPUs from the same series or architecture. The one with the most CUDA cores or Stream processors is the more powerful GPU.
What Do NVIDIA CUDA Cores and AMD Stream Processors Do?
CUDA cores and AMD Stream processors are in charge of pixel processing. It’s thanks to them that you are able to see images or even play games on your laptop or desktop.
CPUs are able to process images and videos. But, GPUs are much better suited to the task. Since they were literally made for image and pixel processing.
Differences Between NVIDIA CUDA Cores and AMD Stream Processors
They are the same but different. Let’s start with what is similar between them. As mentioned earlier, AMD call their GPU cores stream processors and NVIDIA call their CUDA cores.
In the past, NVIDIA used to call them stream processors but they changed that later on. It is all about branding.
They are the same in terms of their function just that the big two tech giants call them differently.
Now for their differences.
This is where GPU architecture comes in. GPU architecture is how the various components of the GPU are put together.
It’s like building a house. It can be a two-bedroom, five-bedroom or a single-bedroom house. You can also choose to include or exclude bricks or wood only. That’s what GPU architecture is like.
NVIDIA GPUs and AMD GPUs have different architectures. Even within the same GPU brand your architectures are different between families or series.
An example is the GTX 1660 Ti which has the NVIDIA Turing architecture and the GTX 1070 which makes use of the Pascal architecture.
And so between companies, they are going to have different GPU architectures.
Differences in GPU architecture mean differences between AMD Stream processors and NVIDIA CUDA cores.
AMD stream processors are smaller and run on lower frequencies whilst NVIDIA CUDA cores are bigger and run on higher frequencies.
AMD Stream Processors
NVIDIA CUDA Cores
Run At Lower Frequencies
Run At High Frequencies
Small in Size
Large In Size
Do The Number of NVIDIA CUDA Cores And AMD Stream Processors Make A Big Difference?
Yes, the number of NVIDIA CUDA Cores and AMD Stream Processors do make a huge difference. Just like the more cores, a CPU has the more powerful it is. The same logic applies to GPUs.
If you are comparing two GPUs from the same company and architecture. The one with more CUDA/Stream processors is going to be the more powerful one.
An RTX 3070 is going to have more CUDA cores than an RTX 3060.
There is a catch though. You can’t compare the performance of two GPUs if they are from different series or companies using the number of stream processors or CUDA cores only.
This is because each company has its own GPU architecture that they use.
This is why you can’t use the CUDA cores or stream processors to solely determine the power of a GPU. This is the reason why benchmarks exist.
A perfect example is the GTX 1070 and RTX 2060. Both have the same amount of CUDA cores. According to Userbenchmark, the RTX 2060 beats the GTX 1070 by 6 per cent.
Yes, the more CUDA cores or stream processors a GPU the more powerful it is. Only if it belongs to the same family.
Using the amount of AMD stream processors and NVIDIA CUDA cores to determine the power of a GPU is a sure way to make wrong conclusions.
This brings us back to the GPU architecture. A major reason for the difference in performance in GPUs.
How Many CUDA Cores Equal a Stream Processor?
Can you convert the number of NVIDIA CUDA cores to AMD stream processors?
There is no way to convert the number of NVIDIA CUDA cores to AMD stream processors. There are no formulas like that.
It’s not even possible. Here’s why.
- GPU architectures are not the same
- The differences we talked about earlier between NVIDIA CUDA cores and AMD stream processors.
Yes, even though we said they are the same i.e have the same function in pixel processing. NVIDIA and AMD took different approaches in making and implementing them in their respective GPU architectures.
So you can’t convert 1920 NVIDIA CUDA cores to X number of stream processors or vice versa. It’s like saying you want to convert an Intel CPU to an AMD CPU. Even though they are both CPUs you can’t do that.
The only true way to know which is better is by benchmarking the GPUs. Benchmarking is the only way to know which is more powerful.
There it is for NVIDIA CUDA cores Vs. AMD Stream Processors. Their functions are similar but the way they are implemented by NVIDIA and AMD results in some differences.
In addition to that, AMD stream processors and NVIDIA CUDA cores are a way to tell how powerful a GPU is.
Although this applies only if they belong to the same GPU architecture or family. A sure way to compare performance is by checking their benchmarks.