Home / GPU Comparison / AMD Radeon R9 M370X Mac Edition or NVIDIA GeForce GTX 1050: What's better?

AMD Radeon R9 M370X Mac Edition

vs

NVIDIA GeForce GTX 1050

GPU Comparison Result

Below are the results of a comparison of AMD Radeon R9 M370X Mac Edition and NVIDIA GeForce GTX 1050 video cards based on key performance characteristics, as well as power consumption and much more.

Advantages

NVIDIA GeForce GTX 1050

Higher Boost Clock: 1455MHz (800MHz vs 1455MHz)
Higher Bandwidth: 112.1 GB/s (72.00 GB/s vs 112.1 GB/s)
Newer Launch Date: October 2016 (May 2015 vs October 2016)

Basic

AMD

Label Name

NVIDIA

May 2015

Launch Date

October 2016

Mobile

Platform

Desktop

Radeon R9 M370X Mac Edition

Model Name

GeForce GTX 1050

Gem System

Generation

GeForce 10

775MHz

Base Clock

1354MHz

800MHz

Boost Clock

1455MHz

PCIe 3.0 x16

Bus Interface

PCIe 3.0 x16

1,500 million

Transistors

3,300 million

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

Samsung

28 nm

Process Size

14 nm

GCN 1.0

Architecture

Pascal

Memory Specifications

2GB

Memory Size

2GB

GDDR5

Memory Type

GDDR5

128bit

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

1125MHz

Memory Clock

1752MHz

72.00 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.

112.1 GB/s

Display and Media

Portable Device Dependent

Outputs

1x DVI
1x HDMI 2.0
1x DisplayPort 1.4a

Theoretical Performance

12.80 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.

46.56 GPixel/s

32.00 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.

58.20 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.

29.10 GFLOPS

64.00 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.

58.20 GFLOPS

1.004 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.

1.899 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.

640

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

16 KB (per CU)

L1 Cache

48 KB (per SM)

256KB

L2 Cache

1024KB

Unknown

TDP

75W

1.2.170

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 (1.2)

OpenCL Version

3.0

4.6

OpenGL

4.6

CUDA

6.1

12 (11_1)

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.

6.5 (5.1)

Shader Model

6.4

Suggested PSU

250W