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AMD Radeon 780M

vs

AMD Radeon RX 5500M

GPU Comparison Result

Below are the results of a comparison of AMD Radeon 780M and AMD Radeon RX 5500M video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

AMD Radeon 780M

Higher Boost Clock: 2900MHz (2900MHz vs 1645MHz)
Newer Launch Date: January 2023 (January 2023 vs October 2019)

AMD Radeon RX 5500M

Larger Memory Size: 4GB (System Shared vs 4GB)
Higher Bandwidth: 224.0 GB/s (System Dependent vs 224.0 GB/s)
More Shading Units: 1408 (768 vs 1408)

Basic

AMD

Label Name

AMD

January 2023

Launch Date

October 2019

Integrated

Platform

Mobile

Radeon 780M

Model Name

Radeon RX 5500M

Navi III IGP

Generation

Mobility Radeon

1500MHz

Base Clock

1375MHz

2900MHz

Boost Clock

1645MHz

PCIe 4.0 x8

Bus Interface

PCIe 4.0 x8

25,390 million

Transistors

6,400 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

4 nm

Process Size

7 nm

RDNA 3.0

Architecture

RDNA 1.0

Memory Specifications

System Shared

Memory Size

4GB

System Shared

Memory Type

GDDR6

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.

128bit

SystemShared

Memory Clock

1750MHz

System Dependent

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.

224.0 GB/s

Display and Media

Portable Device Dependent

Outputs

No outputs

Theoretical Performance

92.80 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.

52.64 GPixel/s

139.2 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.

144.8 GTexel/s

17.82 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.

9.265 TFLOPS

556.8 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.

289.5 GFLOPS

8.731 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.

4.539 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.

1408

128 KB per Array

L1 Cache

2MB

L2 Cache

2MB

15W

TDP

85W

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.

1.3

2.1

OpenCL Version

2.1

4.6

OpenGL

4.6

12 Ultimate (12_2)

DirectX

12 (12_1)

None

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.

6.7

Shader Model

6.5