NVIDIA GeForce GTX 660 vs NVIDIA GeForce GTX 1070
GPU Comparison Result
Below are the results of a comparison of
NVIDIA GeForce GTX 660
and
NVIDIA GeForce GTX 1070
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 1683MHz (1032MHz vs 1683MHz)
- Larger Memory Size: 8GB (2GB vs 8GB)
- Higher Bandwidth: 256.3 GB/s (144.2 GB/s vs 256.3 GB/s)
- More Shading Units: 1920 (960 vs 1920)
- Newer Launch Date: June 2016 (September 2012 vs June 2016)
Basic
NVIDIA
Label Name
NVIDIA
September 2012
Launch Date
June 2016
Desktop
Platform
Desktop
GeForce GTX 660
Model Name
GeForce GTX 1070
GeForce 600
Generation
GeForce 10
980MHz
Base Clock
1506MHz
1032MHz
Boost Clock
1683MHz
PCIe 3.0 x16
Bus Interface
PCIe 3.0 x16
2,540 million
Transistors
7,200 million
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.
120
TSMC
Foundry
TSMC
28 nm
Process Size
16 nm
Kepler
Architecture
Pascal
Memory Specifications
2GB
Memory Size
8GB
GDDR5
Memory Type
GDDR5
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.
256bit
1502MHz
Memory Clock
2002MHz
144.2 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.
256.3 GB/s
Theoretical Performance
20.64 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.
107.7 GPixel/s
82.56 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.
202.0 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.
101.0 GFLOPS
82.56 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.
202.0 GFLOPS
2.021
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.
6.592
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.
15
960
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.
1920
16 KB (per SMX)
L1 Cache
48 KB (per SM)
384KB
L2 Cache
2MB
140W
TDP
150W
1.1
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
3.0
4.6
OpenGL
4.6
3.0
CUDA
6.1
12 (11_0)
DirectX
12 (12_1)
1x 6-pin
Power Connectors
1x 8-pin
5.1
Shader Model
6.4
24
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.
64
300W
Suggested PSU
450W
Benchmarks
FP32 (float)
/ TFLOPS
GeForce GTX 660
2.021
GeForce GTX 1070
6.592
+226%
3DMark Time Spy
GeForce GTX 660
1285
GeForce GTX 1070
5933
+362%
Blender
GeForce GTX 660
126
GeForce GTX 1070
514.06
+308%
Vulkan
GeForce GTX 660
11719
GeForce GTX 1070
49235
+320%
OpenCL
GeForce GTX 660
11135
GeForce GTX 1070
46137
+314%
Hashcat
/ H/s
GeForce GTX 660
25551
GeForce GTX 1070
330579
+1194%