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TensorPool

TensorPool

The easiest way to use cloud GPUs

Website tensorpool.dev
Overview

What it is

Our CLI makes ML model training effortless - just describe your job, and we handle GPU orchestration and execution at half the cost of major cloud providers.

Intent

I need it when

Train large machine learning models quickly without managing infrastructure

TensorPool deploys multi-node GPU clusters in seconds with high-performance networking for distributed training. Users avoid infrastructure setup overhead and pay only for compute hours used, enabling rapid experimentation at lower cost than traditional cloud providers.

Run interactive development and experimentation on GPU clusters with community support

TensorPool offers 24/7 support via Slack, CLI/API interfaces for job and cluster management, and a community for peer support. Users get responsive help and flexible tooling for iterative ML development.

Access high-performance shared storage and object storage colocated with GPU clusters

TensorPool provides shared storage at $100/TB/month with 300 GB/s read speeds and object storage at $50/TB/month with S3 compatibility and no egress charges. Users eliminate data transfer bottlenecks and reduce storage costs.

Scale GPU workloads from single-GPU jobs to 128+ GPUs on demand

TensorPool's Standard Plan provides on-demand access to up to 128 GPUs with a single command, and Enterprise Plan scales to thousands of GPUs. Users can grow workloads without pre-provisioning or long-term commitments.

Reduce GPU compute costs compared to AWS, GCP, and other major cloud providers

TensorPool pricing is 60-75% cheaper than traditional clouds for the same GPU types (e.g., H100 at $1.99/hr vs. $14/hr on GCP). Users achieve significant cost savings while maintaining performance and reliability.

Drop

Not a fit when

  • User needs long-term committed capacity with fixed monthly budgets rather than hourly pay-as-you-go billing
  • User requires GPU types not listed in TensorPool's catalog (B200, H200, B300, H100, L40S, CPU only)
  • User needs on-premises or private cloud deployment instead of cloud-hosted GPU clusters
  • User requires sub-hourly billing granularity or spot instance pricing models
  • User operates in regions where TensorPool infrastructure is not available
Commercials

Pricing

Pay-as-you-go hourly GPU rental with optional storage. Standard Plan: on-demand access to up to 128 GPUs with 24/7 support. Enterprise Plan: custom pricing for scale to thousands of GPUs with dedicated support and SLA. View pricing