Cloud

Starting with the testbed project,
Even live service

The flexible plans cater to diverse needs, providing users
with customizable options that adapt to their unique
requirements and budget constraints.

Monthly
Yearly

Device & Service

  • GPU Chip

  • Time limit

  • Network Tier

  • Storage

Features

  • Project creation

  • Job scheduling

  • Private Network

  • Education

Support

Technical support

FREE

Pay as you go

Everything at your fingertips.

Get Started

  • All

  • Unlimited

  • Choose as you go

  • Choose as you go

  • Choose as you go

  • Doc, Video

Tiered based on usage scale

BASIC

$

Everything at your fingertips.

Get Started

  • Up to NVIDIA RTX 4090

  • 200h/mo

  • Hight

  • 1TB

  • 10

  • -

  • VPC

  • Doc, Video

Chat

pro

$

Everything at your fingertips.

Get Started

  • Up to NVIDIA A100

  • 500h/mo

  • Ultra

  • 5TB

  • Custom

  • Real-time video support

Assignment of dedicated staff

Cost per Device Usage

In addition to subscription plans, paying only for the devices you use
can also be an effective approach.

Cost per Device Usage

Chip Price
  • H100 80GB HBM3
    $1.02/hr
  • H100 PCIe
    $0.97/hr
  • A100-SXM4-80GB
    $0.95/hr
  • A100 80GB PCIe
    $0.94/hr
  • A100-PCIE-40GB
    $0.61/hr
  • GeForce RTX 4090
    $0.31/hr
  • GeForce RTX 3090
    $0.26/hr
  • GeForce RTX 3080
    $0.18/hr

Frequently
Ask
Questions

  • How does a decentralized GPU cloud differ from traditional centralized cloud services?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • How is data security ensured when using decentralized GPU cloud services?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • Is GPU performance consistently delivered?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • What criteria are used to determine rental fees for GPUs?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • Are there latency issues when using GPU resources?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • Can I use GPUs in my preferred region?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • What happens if GPU resources are interrupted during a task?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • How are costs paid, and how can savings be achieved?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

  • How long can I use GPU resources in a decentralized cloud?

    By allowing multiple participants to provide GPUs rather than relying on a single service provider, cost efficiency can be greatly improved. GPGPU utilizes not only its own GPU server centers but also idle GPUs worldwide, offering clients a wide range of options. This allows users to experience the same level of service as traditional cloud platforms while reducing costs.

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