Product characteristics

Based on Tencent Cloud's massive and elastic GPU computing power, it provides plug and play high-performance cloud services

Flexible use

Power off does not charge and supports data retention. It is suitable for dynamic switch on and off according to the use demand, cost saving and long-term use.

One click deployment

Automatically build LLM, AI painting and other application environments at minute level. It provides a variety of pre installed model environments, including popular models such as StableDiffusion and ChatGLM.

Visual interface

It provides a developer friendly graphical interface, supports JupyterLab, WebUI and other computing power connection methods, and has an ultra-low threshold for AI research and debugging.

Application scenarios

Multiple high-performance application deployment scenarios, easy to handle
  • AI Painting
  • AI Conversation/Writing
  • AI development/testing
AI Painting

AI painting is a kind of drawing method that uses deep learning algorithm to create. Widely used in digital media, games, animation, movies, advertising and other fields.

Product advantages
  • Intelligent matching of computing power, multiple computing power packages meet the drawing performance of different needs.
  • Preset mainstream AI painting models and common plug-ins, no need for manual deployment, and support ready to use.
  • Dynamically update the model version to ensure that the model version keeps pace with the times without frequent operations.

Product Comparison

Greatly reduce the threshold of GPU ECS, optimize the product experience from multiple perspectives, and use it out of the box Learn more
GPU ECS
High performance application service HAI
Delivery form
Delivery form
Basic ECS
Delivery form
Plug and play application environment
Model selection
Model selection
Need to know the GPU model, and choose the appropriate model by yourself, there is a risk of mismatch
Model selection
Automatic matching of appropriate packages based on AI applications
Environment deployment
Environment deployment
You need to deploy driver, CUDA, Python, Notebook and other environment dependencies
Environment deployment
Minute level quick start, direct delivery of available application environment
Resource allocation
Resource allocation
Need to purchase additional cloud disk, bandwidth or traffic
Resource allocation
Package GPU, cloud disk, bandwidth and network, and start with one button
Product entrance
Product entrance
Must have some operation and maintenance knowledge, log in the command line interface for operation
Product entrance
Provide visual connection methods such as webui, one click access to services, and visual configuration
Model screening
Model screening
Various models have various versions, which are difficult to choose by oneself
Model screening
Preset the latest version of the mainstream model to adapt to package models
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