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Infrastructure Clouds

Spheron Network

Decentralized GPU/CPU marketplace aggregating 44,000+ nodes at 40–60% below hyperscaler pricing.

What makes Spheron Network different

Spheron operates as a transparent GPU marketplace aggregator rather than a traditional cloud provider. Instead of owning infrastructure, it pools certified data centers globally—44,000+ nodes across 170+ locations—and exposes live, per-minute pricing directly to users. This eliminates the hyperscaler markup: Spheron advertises 40–60% cost savings versus AWS/GCP for identical NVIDIA GPU hardware (H100, H200, B200, B300, A100).

The platform is built on three core commitments: no lock-in contracts, no waitlists, and unified SLA enforcement (99.9% uptime) across all aggregated providers. Standard deployments launch in under 60 seconds. For larger or custom requirements—8–512+ GPU clusters, specific hardware, InfiniBand configs—Spheron sources capacity from its verified network on the user’s behalf with typical 24–48 hour turnaround.

Pricing model

Spheron bills per minute on a usage-based model with no commitments. Live marketplace rates vary by GPU model, region, and provider; the pricing page displays the cheapest current offer for 50+ GPU models sorted by popularity.

For workloads requiring scale or long-term capacity, reserved pricing options lock in lower rates and guaranteed availability. Custom cluster sourcing is available via sales contact. Unlike hyperscalers’ annual commitment discounts, Spheron’s advantage is transparency: pricing is published live, not hidden behind quotes, and users avoid the premium for brand-name infrastructure alone.

When it fits

  • AI/ML training at scale: Cost-sensitive teams training large models (LLMs, vision, diffusion) benefit most from the 40–60% savings on H100/H200 clusters.
  • Batch GPU compute: One-off or periodic compute-heavy jobs (rendering, scientific simulation, data processing) avoid idle hyperscaler costs.
  • Multi-cloud GPU orchestration: Teams needing flexibility across providers or geographic redundancy can manage all instances from a single dashboard.
  • Reserved capacity planning: Projects with known compute timelines (3–12 months) can lock in rates while maintaining no long-term vendor lock-in.
  • Compliance-heavy workloads: ISO 27001, SOC 2 Type I/II, and HIPAA certified data centers support regulated AI applications.

When it doesn’t

Spheron is not a general-purpose cloud platform; it lacks storage, networking, or serverless products. Teams needing integrated databases, managed Kubernetes, or multi-region failover across services should pair Spheron with supplementary providers or stick with hyperscalers.

Inclusion criteria

Spheron meets all three inclusion criteria:

  1. Transparent pricing: Live per-minute rates published on the pricing page with no hidden fees.
  2. Self-service signup: On-demand GPU marketplace available for immediate provisioning without sales gatekeeping.
  3. Public SLA & status: 99.9% uptime SLA published; unified standard across all aggregated providers.