Home / GPU Comparison / Intel Arc B390 or AMD Radeon Vega 11: What's better?

Intel Arc B390

vs

AMD Radeon Vega 11

GPU Comparison Result

Below are the results of a comparison of Intel Arc B390 and AMD Radeon Vega 11 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel Arc B390

More Shading Units: 1536 (1536 vs 704)
Newer Launch Date: January 2026 (January 2026 vs September 2019)

AMD Radeon Vega 11

Higher Boost Clock: 1400MHz (2.5 GHz vs 1400MHz)

Basic

Intel

Label Name

AMD

January 2026

Launch Date

September 2019

Integrated

Platform

Integrated

TSMC N3E

GPU Lithography

Intel Arc B390 GPU

Model Name

Radeon Vega 11

Arc B-Series

Generation

Picasso

300 MHz

Base Clock

300MHz

2.5 GHz

Boost Clock

1400MHz

Bus Interface

IGP

Transistors

4,940 million

RT Cores

12 Xe-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

GlobalFoundries

3 nm

Process Size

14 nm

Xe3

Architecture

GCN 5.0

Memory Specifications

Memory Size

System Shared

Memory Type

System Shared

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

Memory Clock

SystemShared

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

AV1 Encode/Decode

Yes

H.264 Hardware Encode/Decode

Yes

H.265 HEVC Hardware Encode/Decode

Decode Only

H.266 VVC Hardware Encode/Decode

Yes

Intel Quick Sync Video

7680 x 4320 @ 60Hz

Max Resolution DP

3840 x 2400 @ 120Hz

Max Resolution eDP

Number of Displays Supported

eDP 1.5, DisplayPort 2.1 UHBR20, HDMI 2.1 FRL

Outputs

No outputs

Theoretical Performance

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.

11.20 GPixel/s

120 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.

61.60 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.

3.942 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.

123.2 GFLOPS

7.7 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.

2.01 TFLOPS

AI Features

OpenVINO, WindowsML, DirectML, ONNX RT, WebGPU, WebNN

AI Software Frameworks Supported by GPU

122

GPU Peak TOPS (Int8)

Yes

Intel Deep Learning Boost on GPU

Miscellaneous

1536

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.

704

768 KB

L1 Cache

16 MB

L2 Cache

TDP

15W

1.4

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

DirectX 12 Ultimate

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.

Shader Model

6.4