marketplace · container · Layer 2.5
RunPod
Fine-tuning, batch jobs, inference experiments, anyone whose workload can checkpoint and move.
medium portability Movable with effort. Expect to redo images, storage wiring and networking.
What you are buying
- Business model
- Brokers capacity somebody else owns. Cheapest headline rates, and the machine you get is not the machine you chose.
- How you reach it
- You push a container image and it runs. No cluster to operate.
- Accelerators
- H100, H200, A100, L40S, RTX 4090, RTX 5090, and a long consumer tail
- Regions
- Global, community and secure clouds
- Pricing model
- Per-second billing, on-demand and spot. Two tiers: 'Secure Cloud' in real datacentres, 'Community Cloud' on other people's hardware.
- Getting started
- A few dollars.
- Capacity
- Generally good on consumer parts, variable on datacentre parts.
- Ownership
- Private.
Verified 2026-09-09. Fields reading “not published” are exactly that — we do not estimate a figure a vendor withholds.
The counterparty
Low exposure for you: you are renting by the second, so the switching cost of a supplier failing is hours, not quarters. That is the honest advantage of the marketplace model.
A multi-year GPU commitment is a credit decision wearing a cloud contract. This is the section no benchmark covers and the one that decides what happens to your workload in 2028.
The catch
Community Cloud is somebody's machine somewhere. For anything with a compliance story attached, that distinction is the whole decision, and it is easy to miss in the pricing table.
The economics
Reported around $2/hr for an H100 on-demand — roughly a third of CoreWeave list. Per-second billing genuinely matters for bursty work.
No rate is quoted on this page on purpose. Published list prices at this layer move weekly and essentially nobody signing a real contract pays them. Dated, sourced figures live in the GPU rental price index, where the spread between the cheapest and dearest seller of the identical chip runs to roughly 9x.
The layers underneath this one
Whatever you rent here is a chip in a building that needs power. In 2026 megawatts, not silicon, are the binding constraint on the whole industry — a frontier rack draws 120–200 kW against a 2026 average near 27 kW, and the US interconnection queue exceeds 2,600 GW.
Layer 2 — Silicon · Layer 1 — Energy · The interconnection queue · Tokens per watt
Compared against
- Lambda vs RunPod — Real datacentre hourly against per-second marketplace billing.Compare with Lambda
- RunPod vs Vast.ai — Curated marketplace against open bidding: the price gap is the reliability gap.Compare with Vast.ai
- Together AI vs RunPod — Tokens against GPU-hours: the crossover calculation almost nobody does.Compare with Together AI
- TensorDock vs RunPod — Two marketplaces, and how much curation is worth paying for.Compare with TensorDock
- Microsoft Azure (ND, NC) vs RunPod — The widest price gap in the market — roughly $6.98 against roughly $2 for the same H100.Compare with Microsoft Azure (ND, NC)
Related providers
- Akash Network — marketplace, medium portability
- io.net — marketplace, medium portability
- Salad — marketplace, medium portability
- Spheron — marketplace, medium portability
- Vast.ai — marketplace, medium portability
- CUDO Compute — marketplace, medium portability