AMD Radeon RX 6750 GRE 12 GB vs NVIDIA GeForce RTX 4080 Mobile

GPU Comparison Result

Below are the results of a comparison of the characteristics and performance of the AMD Radeon RX 6750 GRE 12 GB and NVIDIA GeForce RTX 4080 Mobile video cards. This comparison will help you determine which one best suits your needs.

Basic

Label Name
AMD
NVIDIA
Launch Date
October 2023
January 2023
Platform
Desktop
Mobile
Model Name
Radeon RX 6750 GRE 12 GB
GeForce RTX 4080 Mobile
Generation
Navi II
GeForce 40 Mobile
Base Clock
2321MHz
1290MHz
Boost Clock
2581MHz
1665MHz
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
2560
7424
SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
-
58
Transistors
17,200 million
35,800 million
RT Cores
40
58
Compute Units
40
-
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
-
232
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
160
232
L1 Cache
128 KB per Array
128 KB (per SM)
L2 Cache
3MB
48MB
Bus Interface
PCIe 4.0 x16
PCIe 4.0 x16
Foundry
TSMC
TSMC
Process Size
7 nm
4 nm
Architecture
RDNA 2.0
Ada Lovelace
TDP
250W
110W

Memory Specifications

Memory Size
12GB
12GB
Memory Type
GDDR6
GDDR6
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
192bit
192bit
Memory Clock
2250MHz
2250MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
432.0 GB/s
432.0 GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
165.2 GPixel/s
133.2 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
413.0 GTexel/s
386.3 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
26.43 TFLOPS
24.72 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
825.9 GFLOPS
386.3 GFLOPS

Miscellaneous

Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.3
1.3
OpenCL Version
2.1
3.0
OpenGL
4.6
4.6
CUDA
-
8.9
DirectX
12 Ultimate (12_2)
12 Ultimate (12_2)
Power Connectors
1x 6-pin + 1x 8-pin
None
Shader Model
6.7
6.7
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
64
80
Suggested PSU
600W
-

Advantages

AMD Radeon RX 6750 GRE 12 GB
Radeon RX 6750 GRE 12 GB
  • Higher Boost Clock: 2581MHz (2581MHz vs 1665MHz)
  • Newer Launch Date: October 2023 (October 2023 vs January 2023)
NVIDIA GeForce RTX 4080 Mobile
GeForce RTX 4080 Mobile
  • More Shading Units: 7424 (2560 vs 7424)

3DMark Time Spy

Radeon RX 6750 GRE 12 GB
13138
GeForce RTX 4080 Mobile
+50% 19674

Blender

Radeon RX 6750 GRE 12 GB
1560
GeForce RTX 4080 Mobile
+308% 6371

SiliconCat Rating

13
Ranks 13 among Mobile GPU on our website
102
Ranks 102 among all GPU on our website
GeForce RTX 4080 Mobile

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