Home / GPU Comparison / Intel Arc 140V or AMD Radeon 780M: What's better?

Intel Arc 140V

vs

AMD Radeon 780M

GPU Comparison Result

Below are the results of a comparison of Intel Arc 140V and AMD Radeon 780M video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

Intel Arc 140V

More Shading Units: 1024 (1024 vs 768)
Newer Launch Date: July 2024 (July 2024 vs January 2023)

AMD Radeon 780M

Higher Boost Clock: 2900MHz (2.05 GHz vs 2900MHz)

Basic

Intel

Label Name

AMD

July 2024

Launch Date

January 2023

Integrated

Platform

Integrated

Intel Arc 140V GPU

Model Name

Radeon 780M

Arc Graphics

Generation

Navi III IGP

400 MHz

Base Clock

1500MHz

2.05 GHz

Boost Clock

2900MHz

Bus Interface

PCIe 4.0 x8

Transistors

25,390 million

RT Cores

8 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

TSMC

3 nm

Process Size

4 nm

Xe2-LPG

Architecture

RDNA 3.0

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

4096 x 2304 @ 60Hz (HDMI 2.1 TMDS), 7680 x 4320 @ 60Hz (HDMI 2.1 FRL)

Max Resolution HDMI

Number of Displays Supported

eDP 1.5, DisplayPort 2.1 UHBR20, HDMI 2.1 FRL

Outputs

Portable Device Dependent

Theoretical Performance

65.6 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.

92.80 GPixel/s

131.2 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.

139.2 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.

17.82 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.

556.8 GFLOPS

4.2 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.

8.731 TFLOPS

AI Features

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

AI Software Frameworks Supported by GPU

GPU Peak TOPS (Int8)

Yes

Intel Deep Learning Boost on GPU

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.

768

L1 Cache

128 KB per Array

8 MB

L2 Cache

2MB

TDP

15W

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

3.0

OpenCL Version

2.1

4.6

OpenGL

4.6

DirectX 12.2

DirectX

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.

Shader Model

6.7