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lambda-labs

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Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

When to use

• Need dedicated GPU instances with full SSH access
• Running long training jobs (hours to days)
• Want simple pricing with no egress fees
• Need persistent storage across sessions
• Require high-performance multi-node clusters (16-512 GPUs)
• Want pre-installed ML stack (Lambda Stack with PyTorch, CUDA, NCCL)
• **GPU variety**: B200, H100, GH200, A100, A10, A6000, V100
• **Lambda Stack**: Pre-installed PyTorch, TensorFlow, CUDA, cuDNN, NCCL

When not to use

• serverless, auto-scaling workloads
• multi-cloud orchestration and cost optimization
• cheaper spot instances and serverless endpoints
• GPU marketplace with lowest prices

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