Radeon Vega 8
AMD Radeon Vega 8 vs Intel Arc A350M
GPU Comparison Result
Below are the results of a comparison of the characteristics and performance of the AMD Radeon Vega 8 and Intel Arc A350M video cards. This comparison will help you determine which one best suits your needs.
Basic
Label Name
AMD
Intel
Launch Date
January 2021
March 2022
Platform
Integrated
Mobile
Model Name
Radeon Vega 8
Arc A350M
Generation
Cezanne
Alchemist
Base Clock
300MHz
300MHz
Boost Clock
2000MHz
1150MHz
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.
512
768
Transistors
9,800 million
7,200 million
RT Cores
-
6
Compute Units
8
-
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.
32
48
L2 Cache
-
4MB
Bus Interface
IGP
PCIe 4.0 x8
Foundry
TSMC
TSMC
Process Size
7 nm
6 nm
Architecture
GCN 5.1
Generation 12.7
TDP
45W
25W
Memory Specifications
Memory Size
System Shared
4GB
Memory Type
System Shared
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.
System Shared
64bit
Memory Clock
SystemShared
1750MHz
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.
System Dependent
112.0 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.
16.00 GPixel/s
27.60 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.
64.00 GTexel/s
55.20 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.
4.096 TFLOPS
3.533 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.
128.0 GFLOPS
441.6 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.
2.047
TFlops
1.801
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.
1.2
1.3
OpenCL Version
2.1
3.0
OpenGL
4.6
4.6
DirectX
12 (12_1)
12 Ultimate (12_2)
Power Connectors
None
-
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.
8
24
Shader Model
6.4
6.6
Advantages
Radeon Vega 8
- Higher Boost Clock: 2000MHz (2000MHz vs 1150MHz)
Arc A350M
- More Shading Units: 768 (512 vs 768)
- Larger Memory Size: 4GB (System Shared vs 4GB)
- Higher Bandwidth: 112.0 GB/s (System Dependent vs 112.0 GB/s)
- Newer Launch Date: March 2022 (January 2021 vs March 2022)
FP32 (float)
Radeon Vega 8
+14%
2.047
TFlops
Arc A350M
1.801
TFlops
3DMark Time Spy
Radeon Vega 8
2742
Arc A350M
+1%
2758
SiliconCat Rating
774
Ranks 774 among all GPU on our website
204
Ranks 204 among Mobile GPU on our website
829
Ranks 829 among all GPU on our website
Arc A350M
