modal-serverless-gpu
Serverless 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.
npx skills add Orchestra-Research/AI-Research-SKILLs --skill modal --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Modal Serverless GPU Comprehensive guide to running ML workloads on Modal's serverless GPU cloud platform. ## When to use Modal **Use Modal when:** - Running GPU-intensive ML workloads without managing infrastructure - Deploying ML models as auto-scaling APIs - Running batch processing jobs (training, inference, data processing) - Need pay-per-second GPU pricing without idle costs - Prototyping ML applications quickly - Running scheduled jobs (cron-like workloads) **Key features:** - **Serverless GPUs**: T4, L4, A10G, L40S, A100, H100, H200, B200 on-demand - **Python-native**: Define infrastructure in Python code, no YAML - **Auto-scaling**: Scale to zero, scale to 100+ GPUs instantly - **Sub-second cold starts**: Rust-based infrastructure for fast container launches - **Container caching**: Image layers cached for rapid iteration - **Web endpoints**: Deploy functions as REST APIs with zero-downtime updates **Use alternatives instead:** - **RunPod**: For longer-running pods with persistent state - **Lambda Labs**: For reserved GPU instances - **SkyPilot**: For multi-cloud orchestration and cost optimization - **Kubernetes**: For complex multi-service architectures ## Quick start
- When to use Modal
- Quick start
- Installation
- Hello World with GPU
- Basic inference endpoint
- Core concepts
- Key components
- Execution modes
- GPU configuration
- Available GPUs
- GPU specification patterns
- Container images
- Persistent storage
- Web endpoints
pip install modal modal setup # Opens browser for authentication Create secret modal secret create huggingface HF_TOKEN=hf_xxx
What does the modal-serverless-gpu skill do?
Serverless 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.
How do I install it?
Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill modal --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.