GeForce RTX 3080 Mobile
NVIDIA GeForce RTX 3080 Mobile vs AMD Radeon RX 7900 GRE
GPU Comparison Result
Below are the results of a comparison of the characteristics and performance of the NVIDIA GeForce RTX 3080 Mobile and AMD Radeon RX 7900 GRE video cards. This comparison will help you determine which one best suits your needs.
Basic
Label Name
NVIDIA
AMD
Launch Date
January 2021
July 2023
Platform
Mobile
Desktop
Model Name
GeForce RTX 3080 Mobile
Radeon RX 7900 GRE
Generation
GeForce 30 Mobile
Navi III
Base Clock
1110MHz
1287MHz
Boost Clock
1545MHz
2245MHz
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.
6144
5120
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.
48
-
Transistors
17,400 million
57,700 million
RT Cores
48
80
Compute Units
-
80
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.
192
-
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.
192
320
L1 Cache
128 KB (per SM)
256 KB per Array
L2 Cache
4MB
6MB
Bus Interface
PCIe 4.0 x16
PCIe 4.0 x16
Foundry
Samsung
TSMC
Process Size
8 nm
5 nm
Architecture
Ampere
RDNA 3.0
TDP
115W
260W
Memory Specifications
Memory Size
8GB
16GB
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.
256bit
256bit
Memory Clock
1750MHz
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.
448.0 GB/s
576.0 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.
148.3 GPixel/s
431.0 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.
296.6 GTexel/s
718.4 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.
18.98 TFLOPS
91.96 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.
296.6 GFLOPS
1437 GFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. 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. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
19.358
TFlops
46.895
TFlops
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
3.0
2.2
OpenGL
4.6
4.6
DirectX
12 Ultimate (12_2)
12 Ultimate (12_2)
CUDA
8.6
-
Power Connectors
None
2x 8-pin
Shader Model
6.6
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.
96
192
Suggested PSU
-
600W
Advantages
GeForce RTX 3080 Mobile
- More Shading Units: 6144 (6144 vs 5120)
Radeon RX 7900 GRE
- Higher Boost Clock: 2245MHz (1545MHz vs 2245MHz)
- Larger Memory Size: 16GB (8GB vs 16GB)
- Higher Bandwidth: 576.0 GB/s (448.0 GB/s vs 576.0 GB/s)
- Newer Launch Date: July 2023 (January 2021 vs July 2023)
FP32 (float)
GeForce RTX 3080 Mobile
19.358
TFlops
Radeon RX 7900 GRE
+142%
46.895
TFlops
Blender
GeForce RTX 3080 Mobile
+10%
3171
Radeon RX 7900 GRE
2883
SiliconCat Rating
18
Ranks 18 among Mobile GPU on our website
141
Ranks 141 among all GPU on our website
28
Ranks 28 among Desktop GPU on our website
51
Ranks 51 among all GPU on our website
Radeon RX 7900 GRE
