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Intel Arc A350M vs AMD Radeon Vega 8 Mobile

Intel Arc A350M

AMD Radeon Vega 8 Mobile

GPU Comparison Result

Below are the results of a comparison of Intel Arc A350M and AMD Radeon Vega 8 Mobile video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel Arc A350M

Larger Memory Size: 4GB (4GB vs System Shared)
Higher Bandwidth: 112.0 GB/s (112.0 GB/s vs System Dependent)
More Shading Units: 768 (768 vs 512)
Newer Launch Date: March 2022 (March 2022 vs January 2021)

AMD Radeon Vega 8 Mobile

Higher Boost Clock: 2000MHz (1150MHz vs 2000MHz)

Basic

Intel

Label Name

AMD

March 2022

Launch Date

January 2021

Mobile

Platform

Integrated

Arc A350M

Model Name

Radeon Vega 8 Mobile

Alchemist

Generation

Cezanne

300MHz

Base Clock

300MHz

1150MHz

Boost Clock

2000MHz

PCIe 4.0 x8

Bus Interface

IGP

7,200 million

Transistors

9,800 million

RT Cores

Compute Units

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.

TSMC

Foundry

TSMC

6 nm

Process Size

7 nm

Generation 12.7

Architecture

GCN 5.1

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

27.60 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

55.20 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

3.533 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

441.6 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

1.801 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.

2.007 TFLOPS

Miscellaneous

768

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

25W

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

4.6

OpenGL

4.6

12 Ultimate (12_2)

DirectX

12 (12_1)

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.

6.6

Shader Model

6.4