Database Mart vs SF Compute: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Database Mart and SF Compute. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Database Mart provides dedicated bare-metal H100, A100, and RTX GPU servers alongside cloud instances for AI, ML, and HPC workloads, with no virtualization overhead for maximum hardware performance. Monthly and on-demand billing options are available, making it suitable for both long-running training jobs and shorter inference workloads that need dedicated GPU hardware. A practical bare-metal GPU option for teams that need consistent, dedicated performance without shared-tenancy concerns.
- Dedicated hardware
- Flexible configurations
- Competitive pricing
- Bare-metal only — requires more infrastructure management
- Limited ML tooling vs managed cloud services
- Smaller ecosystem and fewer integrations
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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.
- 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
- Limited GPU catalog — primarily H100
- Smaller provider — less geographic diversity
- Less mature ecosystem vs established GPU clouds
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Live GPU Pricing
Region Coverage
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Key differences
Database Mart
Dedicated GPU servers
SF Compute
H100 cluster compute — contract and on-demand GPU access from $5.04/hr