Train foundation models without thinking about infrastructure.
Storage infrastructure engineered for distributed training. Optimized for high throughput & low latency workloads with sustained aggregate performance: up to 300 GB/s read, 150 GB/s writes, 1.5M read IOPS, 750k write IOPS.
Training with no orchestration burden. Manage experiments with a familiar push/pull paradigm that eliminates idle GPU time. Normal SSH access also offered.
Prior to delivering our GPUs, TensorPool conducts an extensive burn in process to ensure GPU reliability.
TensorPool provides on-demand multi-node clusters. We do this by scheduling & binpacking users onto TensorPool operated clusters in partnership with compute providers (Nebius, Lightning AI, Verda, Lambda Labs, Google Cloud, Microsoft Azure, and others).