Project Ceiba is an AWS-hosted supercomputer built for NVIDIA’s own AI research and development—not a system customers can rent directly. Announced in November 2023 with a Hopper-based GH200 design, it was upgraded in March 2024 to a Blackwell configuration. AWS’s current project page now says the configuration includes GB300s as well as GB200 systems, but does not state how many GB300s.
What Project Ceiba is—and who it is for
AWS describes Project Ceiba as a collaboration with NVIDIA, hosted on AWS to support NVIDIA’s AI research and development. Its stated research areas include large language models, image, video and 3D generation, simulation, digital biology, robotics, autonomous vehicles and climate prediction. AWS’s Project Ceiba page presents it as a research supercomputer, not a customer-operated cloud service.
How Ceiba changed from Hopper to Blackwell
The companies’ announcements describe two successive configurations. The November 2023 announcement set out the original GH200/Hopper plan; in March 2024, AWS and NVIDIA announced the Blackwell upgrade.
| Announcement | Architecture and system | Accelerators and CPUs | Published performance and networking |
|---|---|---|---|
| November 28, 2023, AWS and NVIDIA | GH200 NVL32, based on Hopper, with Amazon EFA networking | 16,384 GH200 Superchips | No AI-throughput or per-superchip networking rate is specified in the cited announcement. |
| March 18, 2024, AWS and NVIDIA | GB200 NVL72 systems, based on Blackwell | 20,736 B200 GPUs and 10,368 Grace CPUs | 414 exaflops of AI processing; NVIDIA reported up to 800 Gbps per Superchip. |
The March 2024 announcement described the Blackwell upgrade as offering six times the performance of the earlier Hopper plan. That is the companies’ comparison; the cited materials do not provide an independent benchmark methodology for it. NVIDIA’s March 18, 2024 announcement and Amazon’s announcement give the Blackwell configuration details.
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What AWS’s current configuration page says
AWS’s current Ceiba page describes 20,736 Blackwell GPUs and 10,368 Grace CPUs in a GB200 NVL72-based system, and says the configuration includes GB300s as well as 20,736 GB200 Grace Blackwell Superchips. It does not state the number of GB300 systems or say whether the system is fully operational, so the page supports describing GB300s as part of the configuration, not claiming a specific GB300 count or completion date.
What the published performance and networking figures mean
AWS and NVIDIA report 414 exaflops of AI processing for Ceiba, a company-published system specification that AWS continues to list on its current project page. The cited materials do not establish this as an independently measured benchmark.
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Networking figures differ by source and date. NVIDIA’s March 2024 announcement reported up to 800 Gbps per Superchip; AWS’s current page reports 1,600 Gbps per superchip over fourth-generation Elastic Fabric Adapter (EFA). The sources do not explain the difference or establish a shared measurement basis, so these rates should not be treated as a like-for-like comparison. AWS also describes the GB200 NVL72 as a liquid-cooled rack-scale system using fifth-generation NVLink.
Security claims are vendor descriptions, not a full Ceiba audit
AWS says the design integrates NVIDIA Blackwell GPU encryption with AWS Nitro System and EFA to support encrypted AI workloads and isolation of sensitive data. These are vendor descriptions of the design and its intended capabilities, not an independent security assessment of Ceiba as a whole. NVIDIA’s 2024 announcement says the described GB200/Nitro/EFA capability was independently verified by NCC Group; that statement should not be read as an audit of every aspect of Ceiba’s deployment.
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Can customers use Ceiba or get Blackwell compute on AWS?
Ceiba itself is for NVIDIA’s R&D. In their March 2024 announcements, AWS and NVIDIA described separate customer offerings: AWS EC2 instances featuring Blackwell GPUs and NVIDIA DGX Cloud on AWS. Those services are not access to Ceiba. Check AWS and NVIDIA for current availability before choosing or planning a deployment.
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