

We ran the same workloads side by side. The numbers speak for
themselves, and we're not hiding the ones where AWS wins either.
The numbers speak for themselves, and we're not hiding the ones where AWS wins either.

GPU pricing. Consistently 30–40% cheaper on every hardware tier we offer.
Developer simplicity. No IAM rabbit holes, no VPC setup. Run a job in 4 minutes from signup.
Provisioning speed. No quota bureaucracy. Jobs start in under 60 seconds.
Consumer GPU access. RTX 6000s to H200s — accessible for all, not just companies.














Especially from people coming from AWS
We focus exclusively on compute — no S3, no Lambda, no RDS. That focus lets us optimize procurement, infrastructure, and pricing without cross-subsidizing a 200-product cloud ecosystem. We also work with a network of data centers, giving us supply flexibility AWS doesn't have.
If your workload is just GPU compute — training, inference, batch processing — migration is usually a single afternoon. Our CLI is compatible with most standard PyTorch/TF workflows. If you're deeply integrated into AWS services (S3, SageMaker Pipelines), there's more work but we have a migration guide.
We maintain 99.9% uptime SLA across our GPU fleet. For pure training and batch inference workloads, this is more than sufficient. For latency-sensitive, customer-facing inference with strict SLAs, we'd encourage testing thoroughly before full migration.
Yes — monthly commit pricing gets you an additional 20% discount on top of our already-lower base rates. No multi-year lock-in required. Talk to us if you're spending $10K+/month and we'll build a custom plan.
No credit card required to configure your machine. Takes 3 minutes.

Powering the next generation of autonoumous systems with unified Infrastructure.
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