NVIDIA Tesla V100 SXM2 16 GB
vs
NVIDIA H100 SXM5 80 GB
vs
GPU Comparison Result
Below are the results of a comparison of
NVIDIA Tesla V100 SXM2 16 GB
and
NVIDIA H100 SXM5 80 GB
video cards based on key performance characteristics, as well as power consumption and much more.
Advantages
- Higher Boost Clock: 1980MHz (1597MHz vs 1980MHz)
- Larger Memory Size: 80GB (16GB vs 80GB)
- Higher Bandwidth: 3350 GB/s (1133 GB/s vs 3350 GB/s)
- More Shading Units: 16896 (5120 vs 16896)
- Newer Launch Date: March 2022 (November 2019 vs March 2022)
Basic
NVIDIA
Label Name
NVIDIA
November 2019
Launch Date
March 2022
Professional
Platform
Professional
Tesla V100 SXM2 16 GB
Model Name
H100 SXM5 80 GB
Tesla
Generation
Hopper
1245MHz
Base Clock
1590MHz
1597MHz
Boost Clock
1980MHz
PCIe 3.0 x16
Bus Interface
PCIe 5.0 x16
21,100 million
Transistors
80,000 million
640
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
528
320
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.
528
TSMC
Foundry
TSMC
12 nm
Process Size
4 nm
Volta
Architecture
Hopper
Memory Specifications
16GB
Memory Size
80GB
HBM2
Memory Type
HBM3
4096bit
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.
5120bit
1106MHz
Memory Clock
1313MHz
1133 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.
3350 GB/s
Theoretical Performance
204.4 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.
47.52 GPixel/s
511.0 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.
1045 GTexel/s
32.71 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.
1979 TFLOPS
8.177 TFLOPS
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.
34 TFLOPS
16.023
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.
68.248
TFLOPS
Miscellaneous
80
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.
132
5120
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.
16896
128 KB (per SM)
L1 Cache
256 KB (per SM)
6MB
L2 Cache
50MB
250W
TDP
700W
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.
-
3.0
OpenCL Version
3.0
4.6
OpenGL
-
12 (12_1)
DirectX
-
7.0
CUDA
9.0
None
Power Connectors
8-pin EPS
128
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.
24
6.6
Shader Model
-
600W
Suggested PSU
1100W
Benchmarks
FP32 (float)
/ TFLOPS
Tesla V100 SXM2 16 GB
16.023
H100 SXM5 80 GB
68.248
+326%
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