The Most Accurate CPU & GPU Bottleneck Calculator.

The Most Accurate CPU & GPU Bottleneck Calculator.

A significant concern for many computer users is whether there is finally an accurate way to calculate the bottleneck created by their CPU and GPU. Numerous websites attempt to assist users in calculating the bottleneck primarily caused by these two main computer hardware components. However, trusting the results they present without further questioning may leave the landscape blurry regarding how the bottleneck is calculated, potentially leading to confusion due to differing results. In this article, we will break down how you can calculate any bottleneck created between the CPU and GPU yourself. Additionally, we have developed the most accurate CPU & GPU bottleneck calculation method using the most prevalent products on the market.

What is the CPU & GPU Bottleneck?

What is the CPU & GPU Bottleneck?

First of all, let’s acknowledge that CPU and GPU bottlenecking is an inevitable occurrence. While this is more of a theoretical concept since the performance of this computer hardware depends on many factors, it is a common phenomenon. What is useful for any user to know is that when creating a stable computer, the best solution is to minimize the performance difference between the CPU and GPU. They should ideally match as closely as possible in terms of performance. For instance, pairing a quad-core CPU with an RTX 4090 would result in a significant bottleneck on the graphics card side, as it would vastly outperform and be faster than the CPU.

A bottleneck refers to a point in the system where performance is limited or constrained by a single component, resulting in overall system performance being slower than it could be. In the context of CPU and GPU performance, a bottleneck occurs when one of these elements is significantly more powerful or faster than the other, leading to inefficiencies in processing tasks that require both elements to work together.

How to calculate CPU & GPU Bottleneck.

The big question is: how does one calculate the bottleneck between the CPU and GPU? While this question leans more towards theory than practicality, it’s crucial to approach it with realism, relying on modern data. Nonetheless, there exists a formula that enables users to calculate the bottleneck of their own CPUs and GPUs with nearly exact results. Of course, other computer hardware components play their own roles in either exacerbating or alleviating the bottleneck, but the CPU and GPU stand as the primary hardware components, being the fastest ones present in a computer.

The most accurate and recommended approach for calculating the bottleneck between the CPU and GPU is provided by the following formula:

Bottleneck Ratio (%)=(Peak Performance of GPU/ Peak Performance of CPU)/10

The closer the result of this fraction is to 0, the more ideal the combination of CPU and GPU, and the less bottleneck is created between the two.

GPU Peak Performance Calculation.

The method to calculate the peak performance of a GPU is relatively straightforward. For instance, a graphics card like the Nvidia RTX 4090 has a boost clock of 2.52GHz. This number should be multiplied by 2. Thus, we have:

FLOPS per CUDA core=Boost Clock×2=2.52GHz×2=5.04 GFLOPS/core

We then find the number of CUDA cores in the case of Nvidia GPUs (or shaders or stream processors in the case of AMD Radeon GPUs) and multiply them. In the above example, we will have (as the Nvidia RTX 4090 has 16384 CUDA cores):

Total Peak Performance of GPU=4.92 GFLOPS/core×16384 cores=82.575,36

Calculating the Peak Performance of the CPU.

In the case of calculating the CPU peak performance, we should rely on benchmarks that provide a comprehensive measurement of a CPU’s total performance. One such useful tool is provided by Geekbench 4.0, specifically the Geekbench 4 CPU Benchmark suite. CPU benchmark scores from Geekbench 4.0 are utilized to evaluate and optimize CPU and memory performance across various workloads, including artificial intelligence, data compression, image processing, and physics simulation.

Our CPU & GPU bottleneck calculator is based on the Geekbench 4.0 results in terms of CPU performance.

Now, let’s consider an example processor to apply the results to the parsing formula. Take the Ryzen 7 5700X, for instance, which, according to Geekbench 4.0, achieves a score of 592.9 GFLOPS in SGEMM (Single Precision General Matrix Multiplication).

Applying the above formula to determine the bottleneck between the Ryzen 7 5700X and the RTX 4090, we get:

  • Bottleneck Ratio (%)=(Peak Performance of GPU/ Peak Performance of CPU)/10
  • Bottleneck Ratio=(82.575,36/ 592.9)/10= 13.93%

Does screen resolution play a role in the bottleneck between the GPU and CPU?

Yes, that’s why we have included this parameter in our calculator as well. But there is a trick here. When we talk about gaming, for example, the higher the resolution of the screen, the more load the graphics card has to bear for rendering the image. So, the more correct approach is to increase the performance of the graphics card as it requires more resources, allowing more room for the CPU to operate. When we have 1440p resolution, the graphics card load increases by 30%, and it increases by 50% when we’re talking about 4K resolution.

  • At 1080p resolution, no adjustment is needed.
  • At 1440p resolution, the graphics card load increases by 30%, giving this margin to the CPU.
  • At 4K resolution, the graphics card load increases by 50%, giving this margin to the CPU.

When considering other tasks, there are various approaches to determining whether the CPU or GPU will bear a heavier workload, and you should calculate this accordingly.

  1. CPU Load:
    • The CPU may experience a higher load when performing tasks such as rendering complex graphics, processing video data, or handling tasks that involve a lot of calculations, such as image processing or running simulations.
    • Tasks that involve data processing, such as encoding or decoding video streams, may also put a significant load on the CPU.
  2. GPU Load:
    • The GPU tends to handle tasks related to graphics rendering, including screen analysis tasks like rendering high-resolution images, 3D graphics, or applying visual effects.
    • Higher screen resolutions, especially in gaming or graphics-intensive applications, can increase the GPU load as it needs to render more pixels and process more graphical data.
    • GPU-accelerated tasks, such as machine learning inference or certain computational tasks using libraries like CUDA or OpenCL, can also heavily utilize the GPU.

CPU & GPU Bottleneck Calculator.

Based on the data above, we have developed a platform to calculate the bottleneck between the CPU and GPU. We have already included the most prevalent CPUs and GPUs on the market. However, please feel free to leave a comment if you would like us to add other components. Alternatively, you can calculate the bottleneck yourself using the formula mentioned earlier.


This calculator is tailored for gaming. Hence, it’s important to note that as the screen resolution increases, the load shifts towards the GPU.

Final Words.

It’s important to understand that any bottleneck calculator provides a relative approximation rather than an absolute one. The actual bottleneck caused by the CPU and GPU depends on numerous factors and the specific task at hand. In some scenarios, the CPU may be overloaded, while in others, it may be the GPU. Nevertheless, with the formula provided above, you have access to the most accurate method for calculating the bottleneck between the GPU and CPU. Feel free to leave a comment if you require further information or need additional metrics for benchmarking.

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