NVIDIA GeForce GTX 1070 Ti vs NVIDIA GeForce GTX TITAN BLACK
GPU Comparison Result
Below are the results of a comparison of
NVIDIA GeForce GTX 1070 Ti
and
NVIDIA GeForce GTX TITAN BLACK
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 1683MHz (1683MHz vs 980MHz)
- Larger Memory Size: 8GB (8GB vs 6GB)
- Newer Launch Date: November 2017 (November 2017 vs February 2014)
- Higher Bandwidth: 336.0 GB/s (256.3 GB/s vs 336.0 GB/s)
- More Shading Units: 2880 (2432 vs 2880)
Basic
NVIDIA
Label Name
NVIDIA
November 2017
Launch Date
February 2014
Desktop
Platform
Desktop
GeForce GTX 1070 Ti
Model Name
GeForce GTX TITAN BLACK
GeForce 10
Generation
GeForce 700
1607MHz
Base Clock
889MHz
1683MHz
Boost Clock
980MHz
PCIe 3.0 x16
Bus Interface
PCIe 3.0 x16
7,200 million
Transistors
7,080 million
152
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.
240
TSMC
Foundry
TSMC
16 nm
Process Size
28 nm
Pascal
Architecture
Kepler
Memory Specifications
8GB
Memory Size
6GB
GDDR5
Memory Type
GDDR5
256bit
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.
384bit
2002MHz
Memory Clock
1750MHz
256.3 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.
336.0 GB/s
Theoretical Performance
107.7 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.
58.80 GPixel/s
255.8 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.
235.2 GTexel/s
127.9 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.
-
255.8 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.
1.882 TFLOPS
8.022
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.
5.532
TFLOPS
Miscellaneous
19
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.
-
2432
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.
2880
48 KB (per SM)
L1 Cache
16 KB (per SMX)
2MB
L2 Cache
1536KB
180W
TDP
250W
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.
1.1
3.0
OpenCL Version
3.0
4.6
OpenGL
4.6
12 (12_1)
DirectX
12 (11_1)
6.1
CUDA
3.5
1x 8-pin
Power Connectors
1x 6-pin + 1x 8-pin
6.4
Shader Model
5.1
64
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.
48
450W
Suggested PSU
600W
Benchmarks
FP32 (float)
/ TFLOPS
GeForce GTX 1070 Ti
8.022
+45%
GeForce GTX TITAN BLACK
5.532
Blender
GeForce GTX 1070 Ti
626
+37%
GeForce GTX TITAN BLACK
457
OctaneBench
GeForce GTX 1070 Ti
132
+26%
GeForce GTX TITAN BLACK
105
OpenCL
GeForce GTX 1070 Ti
51251
+103%
GeForce GTX TITAN BLACK
25249