AMD Radeon RX 560X Mobile
vs
NVIDIA GeForce GTX 1050 Mobile
vs
GPU Comparison Result
Below are the results of a comparison of
AMD Radeon RX 560X Mobile
and
NVIDIA GeForce GTX 1050 Mobile
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Larger Memory Size: 4GB (4GB vs 2GB)
- More Shading Units: 896 (896 vs 640)
- Newer Launch Date: January 2019 (January 2019 vs January 2017)
- Higher Bandwidth: 112.1 GB/s (112.0 GB/s vs 112.1 GB/s)
Basic
AMD
Label Name
NVIDIA
January 2019
Launch Date
January 2017
Mobile
Platform
Mobile
Radeon RX 560X Mobile
Model Name
GeForce GTX 1050 Mobile
Mobility Radeon
Generation
GeForce 10 Mobile
-
Base Clock
1354MHz
-
Boost Clock
1493MHz
PCIe 3.0 x16
Bus Interface
PCIe 3.0 x16
3,000 million
Transistors
3,300 million
14
Compute Units
-
56
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.
40
GlobalFoundries
Foundry
Samsung
14 nm
Process Size
14 nm
GCN 4.0
Architecture
Pascal
Memory Specifications
4GB
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
1750MHz
Memory Clock
1752MHz
112.0 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
No outputs
Outputs
No outputs
Theoretical Performance
19.57 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.
23.89 GPixel/s
68.49 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.
59.72 GTexel/s
2.192 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.
29.86 GFLOPS
137.0 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.
59.72 GFLOPS
2.236
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.
1.873
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.
5
896
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)
1024KB
L2 Cache
1024KB
65W
TDP
75W
1.2
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
3.0
4.6
OpenGL
4.6
-
CUDA
6.1
12 (12_0)
DirectX
12 (12_1)
None
Power Connectors
None
16
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.
16
6.4
Shader Model
6.4
Benchmarks
FP32 (float)
/ TFLOPS
Radeon RX 560X Mobile
2.236
+19%
GeForce GTX 1050 Mobile
1.873
3DMark Time Spy
Radeon RX 560X Mobile
1864
GeForce GTX 1050 Mobile
2048
+10%
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