NVIDIA Tesla V100 | NVIDIA (2024)

The First Tensor Core GPU

Welcome to the Era of AI.

Finding the insights hidden in oceans of data can transform entire industries, from personalized cancer therapy to helping virtual personal assistants converse naturally and predicting the next big hurricane.


NVIDIA® Tesla® V100 Tensor Coreis the most advanced data center GPU ever built to accelerate AI, high performance computing (HPC), data science and graphics. It’s powered by NVIDIA Volta architecture, comes in 16 and 32GB configurations, and offers the performanceof up to 100 CPUs in a single GPU. Data scientists, researchers, and engineers can now spend less time optimizing memory usage and more time designing the next AI breakthrough.

Run AI and HPC workloads in a virtual environment for better security and manageability using NVIDIA Virtual Compute Server (vCS) software

NVIDIA Tesla V100 | NVIDIA (5)

AI Training

From recognizing speech to training virtual personal assistants and teaching autonomous cars to drive, data scientists are taking on increasingly complex challenges with AI. Solving these kinds of problems requires training deep learning models that are exponentially growing in complexity, in a practical amount of time.

With 640 Tensor Cores, Tesla V100 is the world’s first GPU to break the 100 teraFLOPS (TFLOPS) barrier of deep learning performance. The next generation of NVIDIA NVLink™ connects multiple V100 GPUs at up to 300 GB/s to create the world’s most powerful computing servers. AI models that would consume weeks of computing resources on previous systems can now be trained in a few days. With this dramatic reduction in training time, a whole new world of problems will now be solvable with AI.

NVIDIA Tesla V100 | NVIDIA (6)

AI Inference

To connect us with the most relevant information, services, and products, hyperscale companies have started to tap into AI. However, keeping up with user demand is a daunting challenge. For example, the world’s largest hyperscale company recently estimated that they would need to double their data center capacity if every user spent just three minutes a day using their speech recognition service.

Tesla V100 is engineered to provide maximum performance in existing hyperscale server racks. With AI at its core, Tesla V100 GPU delivers 30X higher inference performance than a CPU server. This giant leap in throughput and efficiency will make the scale-out of AI services practical.

High Performance Computing (HPC)

HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by allowing researchers to analyze large volumes of data for rapid insights where simulation alone cannot fully predict the real world.

Tesla V100 is engineered for the convergence of AI and HPC. It offers a platform for HPC systems to excel at both computational science for scientific simulation and data science for finding insights in data. By pairing NVIDIA CUDA®cores and Tensor Cores within a unified architecture, a single server with Tesla V100 GPUs can replace hundreds of commodity CPU-only servers for both traditional HPC and AI workloads. Every researcher and engineer can now afford an AI supercomputer to tackle their most challenging work.

DATA CENTER GPUs

NVIDIA Tesla V100 | NVIDIA (8)

NVIDIA TESLA V100 FOR NVLINK

Ultimate performance for deep learning.

NVIDIA Tesla V100 | NVIDIA (9)

NVIDIA TESLA V100 FOR PCle

Highest versatility for all workloads.

NVIDIA Tesla V100 Specifications

Tesla V100 for NVLink

Tesla V100 for PCIe

Tesla V100S for PCIe

PERFORMANCE
with NVIDIA GPU Boost

Double-Precision
7.8 teraFLOPS

Single-Precision
15.7 teraFLOPS

Deep Learning
125 teraFLOPS

Double-Precision
7 teraFLOPS

Single-Precision
14 teraFLOPS

Deep Learning
112 teraFLOPS

Double-Precision
8.2 teraFLOPS

Single-Precision
16.4 teraFLOPS

Deep Learning
130 teraFLOPS

INTERCONNECT BANDWIDTH
Bi-Directional

NVLink
300 GB/s

PCIe
32 GB/s

PCIe
32 GB/s

MEMORY
CoWoS Stacked HBM2

CAPACITY
32/16 GB HBM2

BANDWIDTH
900 GB/s

CAPACITY
32 GB HBM2

BANDWIDTH
1134 GB/s

POWER
Max Consumption


300 WATTS


250 WATTS

Take a Free Test Drive

The World's Fastest GPU Accelerators for HPC and Deep Learning.

WHERE TO BUY

Find an NVIDIA Accelerated Computing Partner through our NVIDIA Partner Network (NPN).

NVIDIA Tesla V100 | NVIDIA (2024)

FAQs

NVIDIA Tesla V100 | NVIDIA? ›

Tesla V100 is the flagship product of Tesla data center computing platform for deep learning, HPC, and graphics. The Tesla platform accelerates over 550 HPC applications and every major deep learning framework.

What is Nvidia Tesla V100 used for? ›

Tesla V100 is the flagship product of Tesla data center computing platform for deep learning, HPC, and graphics. The Tesla platform accelerates over 550 HPC applications and every major deep learning framework.

Is the Tesla V100 a good GPU? ›

The deep learning frameworks Caffe, TensorFlow, and CNTK can execute computations up to three times faster on the NVIDIA Tesla V100 compared to the previous model, Tesla P100.

Is nvidia a 100 better than V100? ›

The A100 can achieve up to 312 TFLOPS for AI-specific tasks (using sparsity), substantially increasing over the V100's 125 TFLOPS. This makes the A100 particularly well-suited for training large, complex neural networks. Memory performance is another critical factor in GPU comparison.

How many GPUs does a Tesla V100 have? ›

Powered by NVIDIA Volta™, the latest GPU architecture, Tesla V100 offers the performance of 100 CPUs in a single GPU—enabling data scientists, researchers, and engineers to tackle challenges that were once impossible.

Can you game on an nvidia Tesla V100? ›

The Tesla GPU lineup are meant for productivity but also still can be used for gaming if you wanted to. The reason why it works is because gaming is like a form of 3D modelling it uses the same polygons and geometry rendering used for 3D modelling.

What can you do with a Nvidia Tesla card? ›

Applications. Tesla products are primarily used in simulations and in large-scale calculations (especially floating-point calculations), and for high-end image generation for professional and scientific fields.

How much does a V100 GPU cost per hour? ›

Each V100 GPU is priced as low as $2.48 per hour for on-demand VMs and $1.24 per hour for Preemptible VMs. Like our other GPUs, the V100 is also billed by the second and Sustained Use Discounts apply.

How many CUDA cores does a Tesla V100 have? ›

Powered by NVIDIA's Volta architecture, a single V100 graphics core can offer the performance of almost 32 CPUs. Volta pairs the 5120 CUDA cores and 640 Tensor cores together, allowing a single server of V100S GPUs to replace hundreds of commodity CPU servers for traditional HPC and deep learning.

Is V100 faster than T4? ›

5, V100-PCIe is 3.6x faster than T4. For SSD, V100-PCI is 3.3x – 3.4x faster than T4. For Mask-R-CNN, V100-PCIe is 2.2x – 2.7x faster than T4. With the same number of GPUs, each model almost takes the same number of epochs to converge for T4 and V100-PCIe.

How much power does a Nvidia Tesla V100 GPU use? ›

Being a dual-slot card, the NVIDIA Tesla V100 PCIe 16 GB draws power from 2x 8-pin power connectors, with power draw rated at 300 W maximum.

What is Nvidia's fastest GPU? ›

  • Nvidia GeForce RTX 4070 Super. The best overall GPU right now. ...
  • AMD Radeon RX 7900 GRE. AMD's best overall GPU right now. ...
  • Nvidia GeForce RTX 4070. A finely-balanced high-end Nvidia GPU. ...
  • Nvidia GeForce RTX 4090. The fastest GPU — great for creators, AI, and professionals. ...
  • AMD Radeon RX 7900 XTX. ...
  • Nvidia GeForce RTX 4060.
6 days ago

Which GPU is better, A100, V100 or T4? ›

It is best to use NVIDIA A100 in the field of data science. NVIDIA A100 has the latest Ampere architecture. NVIDIA A30 provides ten times higher speed in comparison to NVIDIA T4. Like NVIDIA A100, NVIDIA V100 also helps in the data science fields.

Is the Nvidia A100 discontinued? ›

Update January 2024: NVIDIA has announced the EOL (End of Life) for the NVIDIA A100 Tensor Core GPU and will discontinue all NVIDIA A100 products including the PCIe and SXM A100 GPUs.

What is the fastest GPU in Tesla? ›

GPU Memory Performance
NVIDIA GPU ModelGPU Memory Bandwidth
Tesla K80480 GB/s
Tesla P40346 GB/s
Tesla P100 12GB549 GB/s
Tesla P100 16GB732 GB/s
13 more rows

How much does an H100 cost? ›

Significantly more than that; MFN pricing for NVIDIA DGX H100 (which has been getting priority supply allocation, so many have been suckered into buying them in order to get fast delivery) is ~$309k, while a basically equivalent HGX H100 system is ~$250k, coming to a price per GPU at the full server level being ~$31.5k ...

What are NVIDIA semiconductors used for? ›

Nvidia (NVDA) introduced graphics processing units, known as GPUs, a key component of PC architecture and large-scale applications. It designs and sells GPUs for gaming, cryptocurrency mining, and professional applications. It also sells chip systems for use in vehicles, robotics, and more.

What is the NVIDIA driver used for? ›

All NVIDIA drivers provide full features and application support for top games and creative applications. If you are a gamer who prioritizes day of launch support for the latest games, patches, and DLCs, choose Game Ready Drivers.

What is the NVIDIA driver for? ›

A NVIDIA driver is a software program that enables communication between your computer and the NVIDIA graphics processor installed in your system. It is used to ensure that your hardware works as intended with the latest software, games and applications.

What are NVIDIA chips used for? ›

Nvidia's high-performance chips now account for four-fifths of gaming GPUs. Happily for Nvidia, its chips have found much wider uses: cryptocurrency mining, self-driving cars and, most important, training of AI models.

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