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NVIDIA GeForce MX550 vs AMD Radeon RX 6600M

NVIDIA GeForce MX550

AMD Radeon RX 6600M

GPU Comparison Result

Below are the results of a comparison of NVIDIA GeForce MX550 and AMD Radeon RX 6600M video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce MX550

Newer Launch Date: January 2022 (January 2022 vs May 2021)

AMD Radeon RX 6600M

Higher Boost Clock: 2416MHz (1320MHz vs 2416MHz)
Larger Memory Size: 8GB (2GB vs 8GB)
Higher Bandwidth: 224.0 GB/s (96.00 GB/s vs 224.0 GB/s)
More Shading Units: 1792 (1024 vs 1792)

Basic

NVIDIA

Label Name

AMD

January 2022

Launch Date

May 2021

Mobile

Platform

Mobile

GeForce MX550

Model Name

Radeon RX 6600M

GeForce MX

Generation

Mobility Radeon

1065MHz

Base Clock

2068MHz

1320MHz

Boost Clock

2416MHz

PCIe 4.0 x8

Bus Interface

PCIe 4.0 x8

4,700 million

Transistors

11,060 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.

112

TSMC

Foundry

TSMC

12 nm

Process Size

7 nm

Turing

Architecture

RDNA 2.0

Memory Specifications

2GB

Memory Size

8GB

GDDR6

Memory Type

GDDR6

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.

128bit

1500MHz

Memory Clock

1750MHz

96.00 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.

224.0 GB/s

Theoretical Performance

21.12 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.

154.6 GPixel/s

42.24 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.

270.6 GTexel/s

2.703 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.

17.32 TFLOPS

42.24 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.

541.2 GFLOPS

2.757 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.

8.832 TFLOPS

Miscellaneous

SM Count

Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.

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.

1792

128 KB (per SM)

L1 Cache

128 KB per Array

2MB

L2 Cache

2MB

25W

TDP

100W

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

3.0

OpenCL Version

2.1

4.6

OpenGL

4.6

7.5

CUDA

12 (12_1)

DirectX

12 Ultimate (12_2)

None

Power Connectors

None

6.6

Shader Model

6.5

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.