Trusted by leading AI organizations
Trusted by leading AI organizations
3FS is specifically designed to handle the unique demands of AI training and inference at scale.
Achieve unprecedented throughput and low latency for large-scale model training with our optimized data access patterns.
Seamlessly scale from single-node deployments to thousands of nodes without performance degradation.
Automatic data replication and recovery ensure training jobs continue even with node failures.
Intelligent caching and prefetching minimize disk I/O bottlenecks during training iterations.
Efficient random access patterns optimized for shuffling large datasets during training.
Native support for TensorFlow, PyTorch, and other popular ML frameworks with minimal configuration.
3FS is built with a modular architecture that separates control and data planes for optimal performance.
Manages file system namespace, access control, and coordinates data placement across the cluster.
Store actual file data with intelligent block placement and replication for fault tolerance.
Provides POSIX-like interface with optimizations for AI workloads, including prefetching and caching.
3FS outperforms traditional distributed file systems for AI workloads.
Than NFS for small random reads common in training data loading.
Than CephFS for metadata operations critical to AI pipelines.
Than Lustre when handling thousands of concurrent clients.
Deploy 3FS in minutes with our simple installation process.
3FS is open source and developed in the open with contributions from users worldwide.
Contribute to the project, report issues, or request features on our GitHub repository.
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