随时随地访问 GPU 零云成本，无需等待
跨实验室、家庭或校园共享闲置 GPU。非常适合需要灵活 GPU 访问但不想支付云费用的学生和开发者。像挂载网络驱动器一样轻松挂载远程 GPU。
为开发者而构建
为您的开发工作流提供本地优先的 GPU 共享，适应您的需求，无论您偏好 CLI、VSCode 还是浏览器界面。
快速
单命令注册和挂载计算设备。自动启动本地和远程工作节点，实现即时访问。
灵活
通过短链接与他人共享 GPU 或跨多个设备访问。完全控制设备配置和分配。
集成
VSCode 集成，插件发布到多个市场。直接在开发环境中完整访问 GPU。
简单
就像使用 NFS 一样使用 GPU。本地优先架构将 GPU 带给您，而不是您去找 GPU。非常适合学生、开发者和小团队。
Key Features
Private Compute Device Registration
Single command to register compute power. Automatically starts Local Worker (shm mode) and Remote Worker (TCP mode).
Compute Mount
Single command to mount registered compute devices. Select available GPUs and confirm mount stub lib path.
Compute Sharing
Share GPUs with others via shortlink. Others can access via browser to automatically add GPU to their account.
VSCode Integration
Publishes plugins to multiple VSCode Marketplaces, automatically completing all functions in VSCode.
Device Configuration and Management
Configure device information, allocation status, load usage, and generate Sharable Links in personal Dashboard.
Use Cases
Students
Borrow idle GPUs from school labs to conduct research, learn new technologies, and experiment with AI models.
Individual Developers
Access GPU resources across multiple devices owned by you, enhancing development experience.
Homelab Enthusiasts
Share computing power within small range (studio, home, school) among individuals or across multiple devices.
Small Startup Teams
Solve supply-demand imbalance for computing power within local network, reducing infrastructure costs.
Pricing Model
Billed by Worker count, subscription-based
Free
- 1 GPU device limit
- No quota control
- Basic sharing features
Personal
- 10 GPU devices limit ($7.9/mo per device)
- Unlimited Workers
- Advanced sharing features
Team
- Unlimited devices ($14.9/mo per device)
- Unlimited Workers
- 7x24 technical support
Get Started with GPU Go
Start sharing GPU resources today and enhance your AI development experience