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Gcore vs SF Compute: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Gcore and SF Compute. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Provider type
Specialist
Specialist
Founded
2014
2023
Headquarters
Luxembourg
San Francisco, CA
Billing model
On-demand, Reserved
On-demand, Contract
Min commitment
None
None (on-demand); contract options available
Support tier
Standard → Enterprise
Standard
Regions
5 regions
1 regions

Strengths & Best For

Gcore

Gcore is a global GPU cloud and CDN provider offering H100, A100, L40S, and L4 instances across 40+ points of presence worldwide, with ultra-low latency networking and built-in DDoS protection for edge AI inference workloads. On-demand and reserved billing options are available, making it a versatile GPU cloud for teams that need both compute and network performance at a global scale. A top choice for latency-sensitive AI inference applications that need to serve users across multiple continents.

Strengths
  • 40+ global PoPs with ultra-low latency networking
  • Built-in DDoS protection
  • H100, A100, L40S, L4 availability
  • CDN + GPU compute in one provider
Weaknesses
  • Smaller provider — limited scale vs hyperscalers
  • Less mature ML tooling vs specialist AI clouds
  • Support quality varies by region
Best For
Global inference deployment needing low latencyLatency-sensitive AI applications serving multiple continentsTeams needing edge compute with DDoS protection
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SF Compute

SF Compute offers H100 SXM5 80GB GPU clusters with both short-term on-demand and longer-term contract pricing. The platform targets AI training and research teams that need reliable H100 access at competitive rates. October 2026 on-demand rate: $5.04/GPU-hr. SF Compute provides VMs, bare metal, and managed Slurm cluster options, making it flexible for different workflow types. A practical choice for teams that want H100 compute without the overhead of hyperscaler pricing.

Strengths
  • H100 SXM5 80GB at competitive on-demand rates
  • Bare metal and managed Slurm options
  • Short and long-term contract flexibility
  • US West region — low latency for West Coast teams
Weaknesses
  • Limited GPU catalog — primarily H100
  • Smaller provider — less geographic diversity
  • Less mature ecosystem vs established GPU clouds
Best For
AI training teams needing H100 clustersResearch teams wanting Slurm-managed GPU computeTeams comparing H100 on-demand rates across providers
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Key differences

Gcore

Global GPU cloud and CDN — H100, A100, L40S across 40+ PoPs worldwide

SF Compute

H100 cluster compute — contract and on-demand GPU access from $5.04/hr

AttributeGcoreSF Compute
Provider typespecialistspecialist
Billing modelOn-demand, ReservedOn-demand, Contract
Min commitmentNoneNone (on-demand); contract options available
Regions5 (EU, US, APAC, +2)1 (US)
Support tierStandard → EnterpriseStandard
Best forGlobal inference deployment needing low latency, Latency-sensitive AI applications serving multiple continentsAI training teams needing H100 clusters, Research teams wanting Slurm-managed GPU compute
Founded / HQ2014 · Luxembourg2023 · San Francisco, CA