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Lambda Labs vs SF Compute: Pricing, Specs, Strengths & Weaknesses

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

Overview

Provider type
Specialist
Specialist
Founded
2012
2023
Headquarters
San Francisco, CA
San Francisco, CA
Billing model
On-demand, Reserved (1yr/3yr), Committed clusters
On-demand, Contract
Min commitment
None (on-demand Instances)
None (on-demand); contract options available
Support tier
Community → Enterprise
Standard
Regions
4 regions
1 regions

Strengths & Best For

Lambda Labs

Lambda (formerly Lambda Labs) is a purpose-built AI supercomputer cloud offering NVIDIA Vera Rubin NVL72, GB300 NVL72, HGX B300, HGX B200, and H200 GPU clusters for large-scale training and inference. Superclusters run on single-tenant infrastructure with NVIDIA Quantum-2 InfiniBand; 1-Click Clusters™ provide production-ready B200 and H100 clusters optimized for distributed workloads; on-demand Instances spin up in minutes for prototyping. SOC 2 Type II certified with single-tenant, shared-nothing architecture. Trusted by leading AI labs and enterprises for frontier model training.

Strengths
  • Vera Rubin NVL72 and GB300 NVL72 supercomputers
  • 1-Click Clusters™ for production-ready B200/H100 distributed workloads
  • Single-tenant, shared-nothing architecture
  • SOC 2 Type II, caged clusters with hardware-level isolation
  • Co-engineering support from infrastructure experts
  • No egress fees
Weaknesses
  • Premium pricing vs commodity GPU clouds
  • Sales-led process for large clusters
  • On-demand Instances have limited availability vs spot-heavy providers
Best For
Frontier model training at scaleEnterprise AI labs needing dedicated supercomputersTeams wanting managed clusters with expert co-engineeringGovernment and regulated industry AI workloads
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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

Lambda Labs — 4 regions
US-EastUS-WestEU-CentralAP-South

Popular Comparisons

Key differences

Lambda Labs

The Superintelligence Cloud — supercomputers for training and inference

SF Compute

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

AttributeLambda LabsSF Compute
Provider typespecialistspecialist
Billing modelOn-demand, Reserved (1yr/3yr), Committed clustersOn-demand, Contract
Min commitmentNone (on-demand Instances)None (on-demand); contract options available
Regions4 (US-East, US-West, EU-Central, +1)1 (US)
Support tierCommunity → EnterpriseStandard
Best forFrontier model training at scale, Enterprise AI labs needing dedicated supercomputersAI training teams needing H100 clusters, Research teams wanting Slurm-managed GPU compute
Founded / HQ2012 · San Francisco, CA2023 · San Francisco, CA