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Thunder Compute
Overview :
Thunder Compute is a GPU cloud service platform focusing on AI/ML development. Using virtualization technology, it helps users access high-performance GPU resources at a very low cost. Its main advantage is its low price, saving up to 80% of the cost compared to traditional cloud service providers. The platform supports various mainstream GPU models, such as NVIDIA Tesla T4, A100, etc., and provides 7+ Gbps network connectivity to ensure efficient data transfer. Thunder Compute aims to reduce hardware costs for AI developers and enterprises, accelerate model training and deployment, and promote the popularization and application of AI technology.
Target Users :
This product primarily targets AI developers, data scientists, machine learning engineers, and enterprises requiring high-performance computing resources. Thunder Compute is an ideal choice for those wishing to reduce hardware costs, quickly set up AI development environments, and accelerate model training and deployment. Its low price and flexible deployment options are especially suitable for startups and research teams with limited budgets.
Use Cases
User @userdotrandom stated that creating an instance, installing, and running the Ollama template through Thunder Compute was very simple.
Dr. Jung Hoon Son stated that transcribing 41 hours of video using an A100 GPU cost only $6.
KronosAI CEO Yujie Huang stated that setting up environments for engineers using Thunder Compute was simpler and saved significant costs compared to AWS.
Features
Provides a selection of various high-performance GPU models to meet different AI/ML development needs.
Achieves cost optimization through virtualization technology, saving 80% of the cost compared to traditional cloud services.
Supports the rapid creation of GPU instances and one-click deployment of commonly used tools (such as Ollama, Comfy-ui).
Provides a simple and easy-to-use user interface and command-line tools to facilitate user creation, management, and monitoring of instances.
7+ Gbps high-speed network connection ensures efficient and stable data transmission.
Instance template function simplifies the process of setting up AI/ML development environments.
Supports hosting on mainstream cloud platforms such as AWS/GCP, providing flexible deployment options.
Provides detailed documentation and community support to help users get started quickly and resolve problems.
How to Use
Visit the Thunder Compute website, register, and log in.
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Select the appropriate GPU model and configuration, and create a GPU instance.
Connect to the created instance via command-line tools or the console.
Use instance templates to quickly install and configure necessary AI tools (such as Ollama).
Begin running model training or AI development tasks.
Monitor the instance's running status via the console or command-line tools.
Adjust instance configurations or expand resources as needed.
Release instance resources to save costs after completing tasks.
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