SF Compute vs Wafer: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for SF Compute and Wafer. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
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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Wafer offers H100 and A100 GPU cloud compute for AI and ML teams with straightforward on-demand pricing and flexible instance options that make it easy to scale training and inference workloads without complex billing structures. Simple setup and transparent pricing lower the barrier to entry for startups and small teams exploring GPU compute for LLM fine-tuning and model deployment. A no-frills on-demand GPU cloud for AI teams that want clear pricing and flexible instance configurations.
- Simple pricing
- Flexible instances
- Fast setup
- Very small provider — limited scale
- No enterprise SLAs
- Limited documentation and support resources
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Key differences
SF Compute
H100 cluster compute — contract and on-demand GPU access from $5.04/hr
Wafer
GPU cloud compute