Reserve Cloud A100 80GB Capacity


Supercharge training and inference from $1.63/hr

From deep learning training to LLM inference, the NVIDIA A100 Tensor Core GPU accelerates the most demanding AI workloads

Up to 4x improvement on ML training over the V100 on the largest models

Up to 5.5x improvement on top HPC apps over the V100

Clusters continuously coming online through Q1 2024.
Reserve access today, or deploy one now from $1.63/hr.

5.5k tokens/sec

Llama 7B inference speed using TensorRT-LLM in FP8

80 GB VRAM at 2,039 GB/s

The A100 SXM has fast, HBM2e memory for ML workloads

From just $1.42/hr

On TensorDock's cloud platform. See below for more pricing details

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About the NVIDIA A100


About the NVIDIA A100 GPU

The NVIDIA A100 is based on NVIDIA's Ampere GPU architecture. It's a powerhouse in the realm of GPUs, catering to demanding applications in AI, data analytics, and high-performance computing.

The A100 is fast. Its 432 third-generation Tensor Cores and 6912 CUDA Cores enable it to providing significant improvements in performance for AI and machine learning applications compared to previous generation GPUs

Apart from pure performance, its massive 80 GB of VRAM and 2 TB/s of memory bandwidth make it ideal for large-scale LLM, data analytics, and scientific computing tasks that require large amounts of fast memory.

The A100 also boasts advanced features like Multi-Instance GPU (MIG), enabling it to efficiently serve multiple workloads simultaneously — up to 7 10GiB VRAM instances per physical GPU. Overall, the NVIDIA A100 represents a significant leap forward in GPU technology, offering strong performance and efficiency for the most demanding computing tasks.

See full data sheet.

5,586 tok/sec LLaMa 7B

A token is a word or subword, so the A100 can generate 19,694 words per second on the LLaMa 7B model. Batch size 384.

6,912 CUDA Cores

CUDA cores are the basic processing units of NVIDIA GPUs. The more CUDA cores, the better.

432 Tensor Cores

Tensor cores are specialized processing units that are designed to efficiently execute matrix operations, used in deep learning.

624 Teraflops FP16

With sparsity.

80 GB VRAM @ 2 TB/s

The more VRAM, the more data a GPU can store at once. The A100 80GB PCIE has 1,935 GB/s of memory bandwidth, while the A100 80GB SXM has 2,039 GB/s.

From just $1.50/hour

Deploy the Powerful NVIDIA A100 GPU on TensorDock

Unleash unparalleled computing power for on the industry's most cost-effective cloud


Deploy up to:

  • 8x NVIDIA A100 SXM4 GPUs for 640 GB of combined VRAM
  • 2x Intel Xeon or AMD EPYC CPUs with 200+ combined threads
  • 27 TB local PCIe 4.0 NVMe SSD
  • 10 Gbps of public internet connectivity

Our hostnodes come with beefy resources, ensuring that your work is never bottlenecked by the hardware resources. We have a select number of hostnodes that we offer on-demand. You can deploy 1-8 GPU A100 virtual machines fully on-demand starting at just $1.63/hour depending on CPU/RAM resources allocated, or $0.67/hour if deployed as a spot instance. We are seeing high demand, so it is difficult to snag a multi-GPU A100 VM at this time.

As such, we higly recommending contacting us to reserve an entire 8x hostnode from an upcoming batch.

Why deploy an NVIDIA A100 on the TensorDock Cloud?


Engineered for Excellence

We built our own hypervisor, our own load balancers, and our own orchestration engine — all so that we can deliver the best performance.

VMs in 10 seconds, not 10 minutes. Instant stock validation. Resource webhooks/callbacks. À la carte resource allocation and resizing.

Save with Storage-Only Pricing

For on-demand servers, when you stop and unreserve your GPUs, you are billed a lower rate for storage. You can always request an export of your VM's disk image.


Jupyter Notebook made easy

Deploy our machine learning image and get Jupyter Notebook/Lab out of the box. Slash your development setup times.

Reliable, Enterprise-Grade Infrastructure

We have multiple data centers across the globe with A100s.

    Devon, United KingdomA100 80GB PCIE
    Tier 1 data center with an unbeatable PUE of only 1.01 incorporating unique cooling technology

    Prague, CzechiaA100 80GB SXM
    Tier 3 data center within the heart of Europe for GDPR compliance, with 24/7 security, redundant power, and multihomed network feeds

    Oregon, United StatesA100 80GB SXM
    Flexential's Tier 3 Hillsboro Oregon data center, with 24/7 security, redundant power, multihomed network feeds, and 100% network and power uptime SLAs

Ask about each data center's compliance certifications. Many are SSAE-18 SOC2 Type II, CJIS, HIPAA, & PCI-DSS certified, so you can trust that your most mission-critical workloads are in a safe place.


More than just A100s.

Hi! We're TensorDock, and we're building a radically more efficient cloud. Five years ago, we started hosting GPU servers in two basements because we couldn't find a cloud suitable for our own AI projects. Soon, we couldn't keep up with demand, so we built a partner network to source supply.

Today, we operate a global GPU cloud with 27 GPU types located in dozens of cities. Some are owned by us, and some are owned by partners, but all are managed by us.

In addition to GPUs, we also offer CPU-only servers.

We speak in tokens and iterations; in IB and TLC/MLC, and we're excited to serve you.







... all deployed within the past 24 hours

Frequenty Asked Questions


Where is the A100 available for deployment?

The A100 is available for deployment at multiple multihomed tier 1-3 data centers. Each is protected by 24/7 security, powered via redundant feeds, and backed a power and network SLA.

Experience sub-20 ms latencies to key population centers along the US west coast for low-latency LLM inference traffic.


How do you guarantee security?

Every layer of our infrastructure is protected by a variety of security measures, ensuring privacy and security for our customers.

Read more about our security.


What virtualization? Docker containers?

We're thrilled to offer bare-metal virtualization for customers looking to rent full 8x configurations for a long period of time.

For on-demand customers, we offer KVM virtualization with root access and a dedicated GPU passed through. You get to use the full compute power of your GPU without resource contention.


How is billing done?

For our on-demand platform, we operate on a pre-paid model: you deposit money and then provision a server. Once your balance nears $0, the server is automatically deleted. For these A100s, we are also earmarking a portion to be billed via long term contracts.

Get started

Deploy an A100 GPU server from $1.42/hour.

Go ahead — go build the future of tomorrow — on TensorDock. Cloud-based machine learning and rendering has never been easier and cheaper.

Deploy a GPU Server

World-class enterprise support

Delivered by dedicated professionals

Deploy your first TensorDock server.

And you'll never look back.

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