Vast.ai vs Lambda Labs — hourly on-demand and spot GPU prices, normalised per single GPU, side by side.
Vast.ai is cheaper on average across the GPU models both providers list (avg $0.5927/GPU/hr vs $1.9550/GPU/hr). Cheaper on average: Vast.ai.
Vast.ai is a marketplace: independent hosts list their own machines and you bid for them. That makes it the cheapest option for interruptible work and for older GPUs, at the cost of more variable reliability and a search-and-bid workflow instead of a fixed catalogue.
Average normalised on-demand price: $0.5927/GPU/hr · 7 listings
Lambda Labs runs its own clusters and is positioned at the higher end: consistent, enterprise-friendly instances on H100/H200 and A100 class hardware, with a simple per-hour price and no marketplace variability. There is no consumer-grade hardware.
Average normalised on-demand price: $1.9550/GPU/hr · 4 listings
| GPU model | VRAM | Vast.ai On-demand /hr | Lambda Labs On-demand /hr | Vast.ai Spot | Lambda Labs Spot | Actions |
|---|
No overlapping GPU models in the current dataset.
For every GPU model both providers list, we compare the normalised single-GPU hourly price. The average of those unit prices is shown for each side, and the lower one is labelled cheaper. We deliberately exclude models only one of the two offers, because that is not a like-for-like comparison.
Not always. Marketplace capacity can be reclaimed at short notice and its hosts vary in network and disk performance, while a dedicated cloud gives more predictable throughput. For multi-node training, interconnect and NVLink support usually matter more than a few cents per hour.
Only roughly. Each platform defines interruption rules, notice periods and reclaim behaviour differently. Treat spot prices as an indication of the cheapest achievable rate, not as a guaranteed price.
Most providers bill by the second or the hour, and per-hour figures are the only ones that can be compared without guessing how many hours you will actually run. Use the GPU cost estimator to convert an hourly rate into a monthly budget.
Reserving large amounts of GPU capacity? Tell us what you need and we will forward your request to the right provider team.