Home / GPU Comparison / AMD Radeon Vega 3 or Intel Iris Xe Graphics 80EU Mobile: What's better?

AMD Radeon Vega 3

vs

Intel Iris Xe Graphics 80EU Mobile

GPU Comparison Result

Below are the results of a comparison of AMD Radeon Vega 3 and Intel Iris Xe Graphics 80EU Mobile video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon Vega 3

Higher Bandwidth: Up to 38.4 GB/s with dual-channel DDR4-2400 (Up to 38.4 GB/s with dual-channel DDR4-2400 vs System Dependent)

Intel Iris Xe Graphics 80EU Mobile

Higher Boost Clock: 1450MHz (Up to 1200 MHz vs 1450MHz)
More Shading Units: 640 (192 vs 640)
Newer Launch Date: January 2023 (January 2018 vs January 2023)

Basic

Intel

Label Name

Intel

January 2018

Launch Date

January 2023

Integrated

Platform

Integrated

Raven Ridge / Picasso

Former Codename

14 nm / 12 nm, APU-dependent

GPU Lithography

AMD Radeon Vega 3

Model Name

Iris Xe Graphics 80EU Mobile

Radeon Vega Mobile

Generation

HD Graphics-M

600 MHz

Base Clock

300MHz

Up to 1200 MHz

Boost Clock

1450MHz

Integrated

Bus Interface

Ring Bus

Transistors

Unknown

RT Cores

Compute Units

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.

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.

GlobalFoundries

Foundry

Intel

14 nm / 12 nm, APU-dependent

Process Size

10 nm

Vega

Architecture

Generation 12.2

Memory Specifications

Shared system memory

Memory Size

System Shared

DDR4 shared system memory

Memory Type

System Shared

Dual-channel system memory, platform dependent

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

Up to DDR4-2400, platform dependent

Memory Clock

SystemShared

Up to 38.4 GB/s with dual-channel DDR4-2400

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

Display and Media

Yes

AMD FreeSync

No hardware support

AV1 Encode/Decode

Encode/Decode

H.264 Hardware Encode/Decode

Encode/Decode

H.265 HEVC Hardware Encode/Decode

No hardware support

H.266 VVC Hardware Encode/Decode

Intel Quick Sync Video

Up to 3, platform dependent

Number of Displays Supported

HDMI, DisplayPort; device dependent

Outputs

Portable Device Dependent

Theoretical Performance

4.8 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.

29.00 GPixel/s

14.4 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.

58.00 GTexel/s

0.92 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.

3.712 TFLOPS

28.8 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.

0.46 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.

1.893 TFLOPS

AI Features

Intel Deep Learning Boost on GPU

Miscellaneous

PCIe 3.0

PCI Express Version

192

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.

640

Shared with processor; typically 15 W APU TDP, 12-25 W configurable

TDP

15W

1.2

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

1.2

OpenCL Version

3.0

4.6

OpenGL

4.6

CUDA

12 (12_1)

DirectX

12 (12_1)

None

Power Connectors

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.

Shader Model

6.6