Buyers of GPU cloud services face a confusing market where five so‑called neoclouds differ in pricing, power capacity, hardware roadmap, contract terms and independent quality scores. CoreWeave, a public company, reports the highest revenue and the only Platinum rating in SemiAnalysis ClusterMAX 2.0, which translates to a 10‑15 % price premium over competitors for managed clusters. Its published on‑demand rates start at $6.16 per H100 GPU‑hour and it offers the most complete price list, including GB200 NVL72 and spot discounts up to 60 %. Nebius, also public, undercuts CoreWeave on Blackwell and is the sole provider publishing B300 on‑demand at $7.85 per GPU‑hour, with preemptible H100 as low as $2.15. It reports $3 billion AI cloud ARR and targets 5 GW contracted power by year‑end. Lambda, still private, lists the lowest B200 on‑demand price at $6.69 per GPU‑hour but lacks a spot tier and relies on sales‑quoted discounts. Crusoe distinguishes itself with AMD MI300X/MI355X availability and the cheapest H200 at $4.29, while reporting 4.9 GW contracted power and a pipeline above 40 GW. Groq has shifted from its LPU chip to become an NVIDIA Cloud Partner, planning to add GPU capacity alongside its token‑based inference service; it does not publish GPU‑hour pricing. For frontier‑scale training, CoreWeave and Nebius offer the proven scale and Vera Rubin NVL72 readiness. Mid‑size jobs benefit from Lambda’s simple on‑demand or Nebius’s preemptible options. Budget experiments find the lowest rates in Nebius spot H100 or CoreWeave spot H100. AMD workloads must go to Crusoe, and high‑volume inference stays with Groq’s per‑token LPU endpoints. Choose based on workload size, latency needs, hardware preference and willingness to commit to long‑term contracts. #AI #Cloud #GPU #Neocloud #Pricing #Innovation