Cheap GPU compute, European rules

What a cheap GPU cloud actually costs

The headline rate is only half of your bill. The other half is how time is rounded, what leaves the meter running, and what gets bolted on at checkout. EponEdge bills GPU time per second: a 12-minute experiment on the $0.12/hr Balanced tier costs about two cents, where hourly rounding would charge you $0.12 for the same work. If your day is twenty short CUDA runs rather than one long one — which is exactly how iterative deep-learning work looks — per-second billing is often a bigger saving than any headline discount.

The rest of the price list fits in one sentence: storage is $0.15/GB/mo, bandwidth is $0.02/GB, and root SSH, JupyterLab and the REST API are included. A 50 GB dataset parked between runs costs $7.50 a month; pulling 20 GB of checkpoints out costs $0.40. You can do this arithmetic before you launch — no egress surprises after the fact.

Grid-aware tiers: flexibility is the discount

Our micro-datacenters sit at the edge of the Belgian grid, powered by renewables. When clean power is abundant, compute is cheap — so instead of one price, there are three. Flexible (from $0.08/hr) follows clean-power availability: it's the first tier paused during a grid event and the last to resume, which makes it the cheapest and lowest-carbon way to rent a GPU here. Balanced (from $0.12) pauses only during severe grid stress, which is rare in practice. Guaranteed (from $0.25) never pauses. Crucially, paused time is never billed, instances resume with processes and GPU memory intact, and every instance keeps the rate it launched at. Checkpointed training, batch inference and overnight jobs get affordable GPU compute for deep learning at a rate that also happens to be the greenest option on the menu.

When we're not the cheapest

Honest answer: if you only chase the lowest possible $/GPU-hr, marketplace spot prices can dip below ours — that's the trade those platforms sell, and for throwaway jobs it can be the right one. EponEdge is dedicated hardware, not a marketplace: no bidding, no unknown hosts, no interruption auctions. And if your workload needs multi-node H100 clusters, we're not your provider — our fleet runs from 24 GB RTX 3090s to 96 GB RTX PRO 6000s, superb value for 7B–13B-class models, image generation and everyday CUDA cloud work, with the EU jurisdiction and GDPR footing marketplaces can't offer.