The Cheapest GPU Cloud

What it does

Compute Cheap offers GPU computing resources on-demand, primarily focused on providing access to high-end NVIDIA chips. Users can rent H100, H200, GB300, or B200 GPUs either as reserved capacity (fixed rate for a guaranteed block) or interruptible capacity (lower cost but subject to reclamation if demand spikes). The service handles provisioning, with users requesting capacity, receiving confirmation, prepaying 50% upfront, and then running workloads on confirmed GPUs.

Who it is for

The service targets teams training and serving large language models. It explicitly appeals to organizations running frontier models that need high-end GPU compute but want to minimize per-unit costs. The interruptible option suits workloads that can tolerate preemptions with proper checkpointing, such as batch training jobs and model merging.

Pricing

H100 SXM 80GB starts at $1.15 per GPU-hour interruptible or $1.19 per GPU-hour reserved. H200 SXM 141GB costs $1.39 per GPU-hour interruptible or $1.99 per GPU-hour reserved. B200 SXM 180GB is priced at $2.29 per GPU-hour interruptible or $3.10 per GPU-hour reserved. GB300 is currently sold out. Minimum reservation is 2,000 GPU-hours per request, with 50% of the block cost prepaid upfront and the remainder billed as usage completes.

How it stands out

The service explicitly positions itself on cost leadership, with a dedicated leaderboard comparing its prices against other GPU cloud providers. It offers interruptible capacity as a lower-cost option for fault-tolerant workloads. The company publishes market benchmarks showing daily pricing comparisons and has published a ranked analysis of GPU cloud pricing across 19 providers. Capacity is geographically available in the United States and European Union regions.

What a founder should check

A potential competitor should investigate switching costs by understanding how many teams actually use interruptible capacity versus reserved, and whether customers build workflows specifically around preemption tolerance. Verify the actual market position by checking whether Compute Cheap consistently maintains the lowest pricing across different GPU types and regions, or if the leaderboard comparisons show volatility. Finally, examine the moat: whether the low prices reflect genuinely lower operational costs or are a temporary positioning strategy, and how sustainable the cost advantage is given that larger cloud providers have their own GPU supply chains and pricing power.