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Canopy WavevsSF Compute

Canopy Wave vs SF Compute: Pricing, Specs, Strengths & Weaknesses

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

Overview

Attribute
Canopy Wave
SF Compute
Provider type
Specialist
Specialist
Founded
2023
2023
Headquarters
United States
San Francisco, CA
Billing model
On-demand, Reserved, Serverless (per-token)
On-demand, Contract
Min commitment
None
None (on-demand); contract options available
Support tier
Standard → Enterprise
Standard
Regions
1 regions
1 regions

Strengths & Best For

Canopy Wave

Canopy Wave announced a merger with SAIHEAT. The platform offers HGX B300 (reserve), GB200 NVL72 (reserve), HGX B200 (reserve), HGX H200, and HGX H100 on-demand. Serverless inference covers DeepSeek V4.1-Flash, DeepSeek V4 Pro, GLM-5.2, Kimi K3, Kimi K2.6, MiniMax M3, and Qwen3.8-Flash-Next. Unlimited Token Plan available. Coding Plan for privacy-protected open model access. Zero data retention policy. Check canopywave.com for current rates.

Strengths
  • H200 and H100 HGX — competitive on-demand pricing
  • Serverless inference: DeepSeek V4 Pro, Kimi K3, GLM-5.2, MiniMax M3
  • Unlimited Token Plan — flat-rate token access
  • Zero data retention policy
  • HGX B300 and GB200 NVL72 available to reserve
  • Merging with SAIHEAT for expanded capacity
Weaknesses
  • Merger with SAIHEAT creates uncertainty
  • Smaller provider — limited scale vs hyperscalers
  • B300/GB200 not yet on-demand (reserve only)
Best For
Teams wanting HGX GPU compute with serverless inferencePrivacy-sensitive workloads (zero data retention)High-volume inference with Unlimited Token PlanTeams needing DeepSeek, Kimi, GLM, MiniMax models
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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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Live GPU Pricing

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Region Coverage

Canopy Wave — 1 regions
US
SF Compute — 1 regions
US

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Provider pages

Canopy Wave pricing and specs SF Compute pricing and specs

Key differences

Canopy Wave

Merging with SAIHEAT — H200, H100, serverless inference with DeepSeek V4 Pro, Kimi K3

SF Compute

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

AttributeCanopy WaveSF Compute
Provider typespecialistspecialist
Billing modelOn-demand, Reserved, Serverless (per-token)On-demand, Contract
Min commitmentNoneNone (on-demand); contract options available
Regions1 (US)1 (US)
Support tierStandard → EnterpriseStandard
Best forTeams wanting HGX GPU compute with serverless inference, Privacy-sensitive workloads (zero data retention)AI training teams needing H100 clusters, Research teams wanting Slurm-managed GPU compute
Founded / HQ2023 · United States2023 · San Francisco, CA