Intel Arc A370M vs AMD Radeon Vega 8
GPU Comparison Result
Below are the results of a comparison of Intel Arc A370M and AMD Radeon Vega 8 video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Larger Memory Size: 4GB (4GB vs System Shared)
- Higher Bandwidth: 112.0 GB/s (112.0 GB/s vs System Dependent)
- More Shading Units: 1024 (1024 vs 512)
- Newer Launch Date: March 2022 (March 2022 vs January 2021)
- Higher Boost Clock: 2000MHz (1550MHz vs 2000MHz)
Basic
Intel
Label Name
AMD
March 2022
Launch Date
January 2021
Mobile
Platform
Integrated
Arc A370M
Model Name
Radeon Vega 8
Alchemist
Generation
Cezanne
300MHz
Base Clock
300MHz
1550MHz
Boost Clock
2000MHz
PCIe 4.0 x8
Bus Interface
IGP
Memory Specifications
4GB
Memory Size
System Shared
GDDR6
Memory Type
System Shared
64bit
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
1750MHz
Memory Clock
SystemShared
112.0 GB/s
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
Theoretical Performance
49.60 GPixel/s
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
99.20 GTexel/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
6.349 TFLOPS
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
793.6 GFLOPS
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
3.237
TFLOPS
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.
2.089
TFLOPS
Miscellaneous
1024
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
4MB
L2 Cache
-
35W
TDP
45W
1.3
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
3.0
OpenCL Version
2.1
Benchmarks
FP32 (float)
/ TFLOPS
Arc A370M
3.237
+55%
Radeon Vega 8
2.089
