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About Modal

Modal provides high-performance AI infrastructure designed for developers to run inference, training, and batch processing with sub-second cold starts and instant autoscaling. It offers a programmable infrastructure where everything is defined in code, eliminating the need for YAML or config files, and ensures environment and hardware requirements are in sync. Modal is built for performance, launching and scaling containers in seconds to maintain tight feedback loops and low latency, and features elastic GPU scaling with access to thousands of GPUs across multiple clouds, scaling to zero when not in use. The platform supports a wide range of ML workloads including deploying and scaling inference for LLMs, audio, and image/video generation; fine-tuning open-source models on single or multi-node clusters; programmatically scaling secure sandboxes for untrusted code; and handling large-scale batch workloads. Modal's AI-native runtime is engineered for heavy AI workloads, offering super-fast autoscaling and model initialization, and includes a built-in, globally distributed storage layer for high-throughput data access. It also provides first-party integrations with existing cloud buckets, MLOps tools, and telemetry vendors, along with multi-cloud capacity and unified observability.