Modal Serverless Gpu
Skill Verified ActiveServerless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
To enable users to run ML workloads on-demand with GPU access without managing infrastructure, by leveraging Modal's serverless platform for deployment and batch processing.
Features
- Serverless GPUs on-demand (T4, A10G, A100, H100, etc.)
- Python-native infrastructure definition
- Auto-scaling for ML workloads
- Deploying ML models as REST APIs
- Running batch processing jobs with automatic scaling
Use Cases
- Running GPU-intensive ML workloads without managing infrastructure
- Deploying ML models as auto-scaling APIs
- Running batch processing jobs (training, inference, data processing)
- Prototyping ML applications quickly
Non-Goals
- Using alternatives like RunPod for longer-running pods with persistent state
- Using Lambda Labs for reserved GPU instances
- Using SkyPilot for multi-cloud orchestration and cost optimization
- Using Kubernetes for complex multi-service architectures
Installation
First, add the marketplace
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs/plugin install AI-Research-SKILLs@ai-research-skillsQuality Score
VerifiedTrust Signals
Similar Extensions
Cloudflare Deploy
99Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.
Render Deploy
99Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.
Cost Optimization
98Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
Skypilot Multi Cloud Orchestration
98Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
Modal Serverless Gpu
98Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
RunPod Cloud GPU
98Cloud GPU processing via RunPod serverless. Use when setting up RunPod endpoints, deploying Docker images, managing GPU resources, troubleshooting endpoint issues, or understanding costs. Covers all 5 toolkit images (qwen-edit, realesrgan, propainter, sadtalker, qwen3-tts).