NVIDIA GRID K160Q vs NVIDIA Tesla V100 FHHL

VS

NVIDIA GRID K160Q

NVIDIA Tesla V100 FHHL

We compared two Professional market GPUs: 1024MB VRAM GRID K160Q and 16GB VRAM Tesla V100 FHHL to see which GPU has better performance in key specifications, benchmark tests, power consumption, etc.

Main Differences

NVIDIA GRID K160Q 's Advantages

Lower TDP (130W vs 250W)

NVIDIA Tesla V100 FHHL 's Advantages

Released 4 years and 9 months late

Boost Clock1290MHz

More VRAM (16GB vs 1024GB)

Larger VRAM bandwidth (829.4GB/s vs 28.51GB/s)

4928 additional rendering cores

Score

Benchmark

FP32 (float)

GRID K160Q

0.326 TFLOPS

Tesla V100 FHHL +3952%

13.21 TFLOPS

GRID K160Q

VS

Tesla V100 FHHL

Graphics Card

Jun 2013

Release Date

Mar 2018

GRID

Generation

Tesla

Professional

Type

Professional

PCIe 3.0 x16

Bus Interface

PCIe 3.0 x16

Clock Speeds

-

Base Clock

937 MHz

-

Boost Clock

1290 MHz

891 MHz

Memory Clock

810 MHz

Memory

1024MB

Memory Size

16GB

DDR3

Memory Type

HBM2

128bit

Memory Bus

4096bit

28.51GB/s

Bandwidth

829.4GB/s

Render Config

-

SM Count

80

192

Shading Units

5120

16

TMUs

320

16

ROPs

128

-

Tensor Cores

640

-

16 KB (per SMX)

L1 Cache

128 KB (per SM)

256 KB

L2 Cache

6 MB

-

Theoretical Performance

3.400 GPixel/s

Pixel Rate

165.1 GPixel/s

13.60 GTexel/s

Texture Rate

412.8 GTexel/s

-

FP16 (half)

26.42 TFLOPS

326.4 GFLOPS

FP32 (float)

13.21 TFLOPS

13.60 GFLOPS

FP64 (double)

6.605 TFLOPS

Board Design

130W

TDP

250W

300 W

Suggested PSU

600 W

No outputs

Outputs

No outputs

-

Power Connectors

1x 8-pin

Graphics Processor

GK107

GPU Name

GV100

-

Kepler

Architecture

Volta

TSMC

Foundry

TSMC

28 nm

Process Size

12 nm

1.27 billion

Transistors

21.1 billion

118 mm²

Die Size

815 mm²

Graphics Features

12 (11_0)

DirectX

12 (12_1)

4.6

OpenGL

4.6

3.0

OpenCL

3.0

1.1

Vulkan

1.3

3.0

CUDA

7.0

5.1

Shader Model

6.6

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