NVIDIA GeForce GTX 1060 6 GB Rev. 2 vs AMD Radeon 760M
GPU Comparison Result
Below are the results of a comparison of NVIDIA GeForce GTX 1060 6 GB Rev. 2 and AMD Radeon 760M video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Larger Memory Size: 6GB (6GB vs System Shared)
- Higher Bandwidth: 192.2 GB/s (192.2 GB/s vs System Dependent)
- More Shading Units: 1280 (1280 vs 384)
- Higher Boost Clock: 2800MHz (1709MHz vs 2800MHz)
- Newer Launch Date: January 2023 (January 2018 vs January 2023)
Basic
NVIDIA
Label Name
AMD
January 2018
Launch Date
January 2023
Desktop
Platform
Integrated
GeForce GTX 1060 6 GB Rev. 2
Model Name
Radeon 760M
GeForce 10
Generation
Navi III IGP
1506MHz
Base Clock
1500MHz
1709MHz
Boost Clock
2800MHz
PCIe 3.0 x16
Bus Interface
PCIe 4.0 x8
4,400 million
Transistors
25,390 million
-
RT Cores
6
-
Compute Units
8
80
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.
24
TSMC
Foundry
TSMC
16 nm
Process Size
4 nm
Pascal
Architecture
RDNA 3.0
Memory Specifications
6GB
Memory Size
System Shared
GDDR5
Memory Type
System Shared
192bit
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.
System Shared
2002MHz
Memory Clock
SystemShared
192.2 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.
System Dependent
Theoretical Performance
82.03 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.
44.80 GPixel/s
136.7 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.
67.20 GTexel/s
68.36 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.
8.602 TFLOPS
136.7 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.
268.8 GFLOPS
4.287
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.
4.387
TFLOPS
Miscellaneous
10
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.
-
1280
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.
384
48 KB (per SM)
L1 Cache
128 KB per Array
1536KB
L2 Cache
2MB
120W
TDP
15W
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
12 (12_1)
DirectX
12 Ultimate (12_2)
6.1
CUDA
-
1x 6-pin
Power Connectors
None
48
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
6.7
300W
Suggested PSU
-
Benchmarks
FP32 (float)
/ TFLOPS
GeForce GTX 1060 6 GB Rev. 2
4.287
Radeon 760M
4.387
+2%
