NVIDIA GeForce GT 1030 vs NVIDIA GeForce GTX 560
GPU Comparison Result
Below are the results of a comparison of
NVIDIA GeForce GT 1030
and
NVIDIA GeForce GTX 560
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Larger Memory Size: 2GB (2GB vs 1024MB)
- More Shading Units: 384 (384 vs 336)
- Newer Launch Date: May 2017 (May 2017 vs May 2011)
- Higher Bandwidth: 128.0 GB/s (48.06 GB/s vs 128.0 GB/s)
Basic
NVIDIA
Label Name
NVIDIA
May 2017
Launch Date
May 2011
Desktop
Platform
Desktop
GeForce GT 1030
Model Name
GeForce GTX 560
GeForce 10
Generation
GeForce 500
1228MHz
Base Clock
-
1468MHz
Boost Clock
-
PCIe 3.0 x4
Bus Interface
PCIe 2.0 x16
1,800 million
Transistors
1,950 million
24
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.
56
Samsung
Foundry
TSMC
14 nm
Process Size
40 nm
Pascal
Architecture
Fermi 2.0
Memory Specifications
2GB
Memory Size
1024MB
GDDR5
Memory Type
GDDR5
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.
256bit
1502MHz
Memory Clock
1000MHz
48.06 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.
128.0 GB/s
Theoretical Performance
23.49 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.
11.34 GPixel/s
35.23 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.
45.36 GTexel/s
17.62 GFLOPS
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.
-
35.23 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.
90.72 GFLOPS
1.104
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.
1.067
TFLOPS
Miscellaneous
3
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.
7
384
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.
336
48 KB (per SM)
L1 Cache
64 KB (per SM)
512KB
L2 Cache
512KB
30W
TDP
150W
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.
N/A
3.0
OpenCL Version
1.1
4.6
OpenGL
4.6
12 (12_1)
DirectX
12 (11_0)
6.1
CUDA
2.1
None
Power Connectors
2x 6-pin
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.
32
6.4
Shader Model
5.1
200W
Suggested PSU
450W
Benchmarks
FP32 (float)
/ TFLOPS
GeForce GT 1030
1.104
+3%
GeForce GTX 560
1.067
Hashcat
/ H/s
GeForce GT 1030
53248
+69%
GeForce GTX 560
31509
Share in social media
Or Link To Us
<a href="https://cputronic.com/gpu/compare/nvidia-geforce-gt-1030-vs-nvidia-geforce-gtx-560" target="_blank">NVIDIA GeForce GT 1030 vs NVIDIA GeForce GTX 560</a>