Akamai Cloud vs SF Compute: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Akamai Cloud and SF Compute. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Akamai Cloud (formerly Linode) offers RTX 4090 and A100 GPU instances backed by Akamai's global CDN and edge network, providing strong network performance and competitive on-demand pricing for AI inference workloads that need global distribution. Available across multiple regions worldwide, it is a natural fit for teams already using Akamai's CDN who want to co-locate GPU inference close to their edge infrastructure. A solid GPU cloud option for inference-heavy applications where network latency and global reach matter.
- Global edge network
- Competitive pricing
- Multiple regions
- Strong network performance
- Very limited GPU catalog — primarily older GPU SKUs
- Not ML-focused — limited AI tooling
- No spot/preemptible GPU options
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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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Key differences
Akamai Cloud
Global edge GPU cloud backed by Akamai's CDN network
SF Compute
H100 cluster compute — contract and on-demand GPU access from $5.04/hr