neocloud · vm · Layer 2.5
Lambda
Researchers and small teams who want a real GPU in the next ten minutes without a procurement conversation.
medium portability Movable with effort. Expect to redo images, storage wiring and networking.
What you are buying
- Business model
- Purpose-built GPU cloud. Owns or leases its own datacentre capacity and sells it directly.
- How you reach it
- You get virtual machines. The familiar cloud model.
- Accelerators
- H100, H200, B200, GH200, A100
- Regions
- US
- Pricing model
- On-demand by the hour, plus reserved clusters. Pricing is published on the website, which is rarer at this layer than it should be.
- Getting started
- Credit card, single GPU, minutes.
- Capacity
- Frequently sold out on the newest parts. Availability is the constraint, not price.
- Ownership
- Private, widely reported as IPO-track.
Verified 2026-09-09. Fields reading “not published” are exactly that — we do not estimate a figure a vendor withholds.
The counterparty
Private, so you are diligencing a company that does not have to tell you anything. Reported among the group carrying GPU-collateralised debt maturing 2026-2028.
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
The thing you want is often unavailable. Reserved capacity solves it and turns the credit-card product into a contract.
The economics
Among the lowest published rates on the newest silicon — reported lowest on B200 in an August 2026 comparison. Cheap when you can get it.
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
- CoreWeave vs Lambda — Contracted scale against credit-card speed — and a list price roughly three times higher.Compare with CoreWeave
- Lambda vs RunPod — Real datacentre hourly against per-second marketplace billing.Compare with RunPod
- SF Compute vs Lambda — Buying a market window against buying a reservation.Compare with SF Compute
Related providers
- Crusoe — neocloud, medium portability
- DataCrunch — neocloud, medium portability
- Genesis Cloud — neocloud, medium portability
- Hyperstack (NexGen Cloud) — neocloud, medium portability
- Nebius — neocloud, medium portability
- Paperspace (DigitalOcean) — neocloud, medium portability