{"id":"modal-api","name":"Modal","homepage":"https://modal.com/docs/reference/modal.Client","repo_url":"https://github.com/modal-labs/modal-client","category":"ai-ml","subcategories":["serverless-gpu","cloud-compute","ml-infrastructure","python"],"tags":["modal","serverless-gpu","gpu-compute","ml-infrastructure","python","containers","batch-processing","ai"],"what_it_does":"Serverless cloud compute platform for running Python functions on demand with GPU acceleration, enabling ML inference, training, and data processing without infrastructure management.","use_cases":["Serverless GPU inference for custom ML models without managing GPU servers","Burst processing for AI workloads that need compute on demand","Running data pipelines and batch jobs with auto-scaling GPU workers","Hosting custom ML model inference APIs with automatic scaling","Fine-tuning and training ML models on ephemeral GPU clusters"],"not_for":["Always-on latency-sensitive services (Modal has cold start overhead)","Non-Python workloads (Modal is Python-first)","Simple CPU-bound tasks where cheaper compute suffices"],"best_when":"You need serverless GPU compute for Python ML workloads without the DevOps overhead of managing CUDA environments, Docker, or Kubernetes.","avoid_when":"You need always-on low-latency inference, non-Python runtimes, or predictable fixed costs.","alternatives":["replicate-api","huggingface-api","lambda-labs-api"],"af_score":83.8,"security_score":null,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"current","last_evaluated":"2026-03-01T09:50:05.958699+00:00","performance":{"latency_p50_ms":2000,"latency_p99_ms":15000,"uptime_sla_percent":99.9,"rate_limits":"No explicit rate limits; queued execution based on available GPU capacity","data_source":"llm_estimated","measured_on":null}}