Cirrascale vs Oblivus: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Cirrascale and Oblivus. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
- H100/H200 cluster focus
- InfiniBand networking
- Dedicated deployments
- Enterprise SLAs
- Bare-metal focused — requires more infrastructure management
- Limited self-service tooling
- Smaller ecosystem vs cloud providers
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Oblivus is a GPU cloud offering H200, H100 SXM5, H100 NVLink, H100 PCIe, A100 NVLink, A100 PCIe, L40, RTX 4090, and RTX A6000 instances with transparent all-in pricing (vCPUs, RAM, and storage included). Reservation pricing available for H100 SXM5. Price is locked at deployment — if prices decrease, you benefit; if they increase, your rate stays unchanged. RTX 5090 now available on demand. No spot instances — dedicated instances only.
- Price locked at deployment — protected from future price increases
- All-in pricing: vCPUs, RAM, storage included — no hidden fees
- H200, H100 SXM5, A100 — competitive dedicated pricing
- RTX 5090 now available on demand
- Dedicated instances only — no noisy-neighbor effects
- Free data ingress and egress
- No spot instances — dedicated only (higher minimum cost)
- Smaller provider — limited scale vs hyperscalers
- Limited documentation and support resources
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Key differences
Cirrascale
Enterprise AI infrastructure with H100 and H200 clusters
Oblivus
H200, H100 SXM, A100, RTX 4090 — price locked at deployment