The AI Compute Race report costs GPU compute exterior the largest patrons: a three-year dedication cuts the median worth by 48%, whereas 17 of twenty-two tracked GPU fashions rose in worth over the previous 12 months
DALLAS, Texas – November 13, 2026 – Fluence has printed The AI Compute Race, a report that costs GPU cloud compute for each firm that’s not a frontier lab or a hyperscaler. It was produced with analysis companions NEAR AI, io.web, Boundless, Phala, Gensyn, Fortytwo, Theta, Compute Labs and GAIB. Its central discovering: the place an organization buys a GPU-hour units the value. Throughout H100, H200 and B200 fashions, hyperscalers listing GPUs at 1.98 instances the GPU-cloud median, from 1.4 instances on the B200 to 2.8 instances on the H100. The identical H200 lists from $4.08 to $10.60 an hour.
Dedication size issues nearly as a lot as supplier selection. Towards every supplier’s personal on-demand fee, a one-year reservation cuts the median worth by 21% and a three-year time period by 48%. Spot capability lists at 53% of on-demand, for workloads that may be interrupted.
Consumers who count on GPU costs to fall could have to recheck their budgets. Seventeen of the 22 GPU fashions tracked by GetDeploying value greater than a 12 months earlier, and the median H100 rents for 13% to 30% extra, relying on the window measured.
The report additionally traces why costs are quickly rising:
Demand moved to open fashions. Chinese language fashions’ share of OpenRouter tokens amongst firms within the US, Europe and the International South rose from 6–13% to 57–67% in underneath eight months, based on CNBC. Open weights let any firm with GPUs serve a near-frontier mannequin on {hardware} it controls.
The most important patrons locked up the latest provide. The 4 largest hyperscalers information $720–740 billion of 2026 capital spending, and the 4 largest disclosed offers by AI labs and Meta with neoclouds complete about $233 billion, three of them “as much as” quantities and far of it for capability not but delivered.
The GPU-hour is changing into a monetary asset. CME, ICE and Nodal Change have introduced GPU futures, every deciding on a unique worth index, whereas lenders are already lending towards GPUs: Lambda’s investment-grade-rated mortgage priced at 6.78% and Sharon AI’s, with no ranking disclosed, at 9.95%.
“Open-weight fashions are shut behind the perfect closed ones, and firms are switching to them. Any firm with GPUs can now serve a near-frontier mannequin on {hardware} it controls. The GPUs are the onerous half,” stated Evgeny Ponomarev, Co-founder of Fluence.
The report closes with 4 methods to pay much less for a similar compute: examine the identical chip throughout supplier sorts, commit when the workload is regular, match the GPU technology to the mannequin, and look past the hyperscalers, since a lot of the latest neocloud capability is contracted to labs years forward.
The total report is offered at fluence.ai/compute-race-2026.
About Fluence
Fluence Cloud is a GPU cloud supplier with capability from unbiased information facilities (fluence.ai). Based in 2017 by Dmitry Kurinskiy, Evgeny Ponomarev and Tom Trowbridge, the corporate has raised $14 million from traders together with 1KX, Multicoin, Distributed International, Blockchange, Tiger International and Protocol Labs.
