Radeon Vega 8
AMD Radeon Vega 8 vs Intel Arc A380M
GPU Comparison Result
Below are the results of a comparison of the characteristics and performance of the AMD Radeon Vega 8 and Intel Arc A380M video cards. This comparison will help you determine which one best suits your needs.
Basic
Label Name
AMD
Intel
Launch Date
January 2021
January 2023
Platform
Integrated
Mobile
Model Name
Radeon Vega 8
Arc A380M
Generation
Cezanne
Alchemist
Base Clock
300MHz
1550MHz
Boost Clock
2000MHz
2000MHz
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
1024
Transistors
9,800 million
7,200 million
RT Cores
-
8
Compute Units
8
-
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.
-
128
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
64
L2 Cache
-
4MB
Bus Interface
IGP
MXM-A (3.1)
Foundry
TSMC
TSMC
Process Size
7 nm
6 nm
Architecture
GCN 5.1
Generation 12.7
TDP
45W
35W
Memory Specifications
Memory Size
System Shared
6GB
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
96bit
Memory Clock
SystemShared
1937MHz
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
186.0 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
64.00 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
128.0 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
8.192 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
1024 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
4.095
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
32
Shader Model
6.4
6.6
Advantages
Arc A380M
- More Shading Units: 1024 (512 vs 1024)
- Larger Memory Size: 6GB (System Shared vs 6GB)
- Higher Bandwidth: 186.0 GB/s (System Dependent vs 186.0 GB/s)
- Newer Launch Date: January 2023 (January 2021 vs January 2023)
FP32 (float)
Radeon Vega 8
2.047
TFlops
Arc A380M
+100%
4.095
TFlops
SiliconCat Rating
775
Ranks 775 among all GPU on our website
125
Ranks 125 among Mobile GPU on our website
553
Ranks 553 among all GPU on our website
Arc A380M
