Qubrid AI is listed here as a hybrid quantum-classical platform that also rents GPUs. Founded in 2022, headquarters San Jose, California. Status is active. Billing is per hour and the recorded payment method is credit card. The scraped GPU rows are ordinary NVIDIA parts: B200, H200, H100 SXM, A100 (80GB and 40GB), and L40S. This page does not try to describe a quantum product we have not scraped.
Why Qubrid AI stands out
The previous write-up said the GPU list and the developer tools were missing. They are not. The data card records an API, Docker, Jupyter, persistent storage, and multi-GPU. Kubernetes, spot, reserved instances, and SOC 2 are not set.
Compare the hourly rows on this page with other clouds that list the same slugs. That is the useful question. The quantum side of the tagline is not something this scrape verifies.
Pros
- Published datacenter GPUs, including B200, H200, H100 SXM, A100, and L40S
- Per-hour billing and credit card, with a 2022 founding date and a San Jose headquarters on file
- API, Docker, Jupyter, persistent storage, and multi-GPU recorded
Cons
- No Kubernetes, no spot, and no reserved instances in our data
- Not marked SOC 2 compliant
- Enterprise readiness in our scoring is low. This is a small GPU catalogue, not a hyperscaler
- The hybrid quantum claim is the provider’s positioning. Our scrape only covers the GPU price list
Getting started
- Open Qubrid AI and separate the GPU catalogue from any quantum product you are not here for.
- Create an account with a credit card.
- Match an hourly row on this page (H100 SXM or A100 are the usual comparison points) to the instance on their console.
- Deploy with Docker or Jupyter. Both are recorded. Do not plan on Kubernetes or spot from what we have.
Best for: Someone comparing hourly H100, H200, A100, or B200 rentals who also wants Jupyter and an API, and who does not need Kubernetes, spot, or SOC 2.