Overview
Strengths & Best For
Cerebrium is a serverless ML infrastructure platform that deploys H100, A100, and T4 GPU workloads in seconds using custom containers, enabling real-time LLM inference and fine-tuned model serving without managing any infrastructure. Per-second billing and fast cold starts (typically under 5 seconds) make it highly cost-efficient for bursty AI inference APIs and model deployment pipelines. Supports any Python framework — PyTorch, TensorFlow, JAX, vLLM, TGI. Free tier available. A top choice for ML teams that want to ship production inference endpoints quickly with minimal DevOps overhead.
- Cold starts under 5 seconds — fast serverless GPU spin-up
- Custom containers — any Python framework supported
- Per-second billing with free tier
- H100 and A100 availability
- Supports vLLM, TGI, and custom inference servers
- Smaller provider — limited cluster scale
- Fewer regions than major cloud providers
- Not suitable for multi-node distributed training
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Lium (operated by Datura AI Corp) is a GPU marketplace offering H100, H200, A100, and other GPU nodes with per-second billing and no minimum rental period. A prepaid balance sufficient to cover 15 minutes is required to start a rental; billing stops the moment you end it. Spot and secure node tiers are available. Check the live table for current availability and rates.
- Per-second billing — pay only for what you use
- Minimum rentable GPUs varies by node — single GPUs to whole 8-GPU nodes
- Spot and secure node tiers
- H100, H200, A100 and other GPU models available
- Marketplace prices move as nodes rent out
- Marketplace model — hardware availability varies by node
- Smaller provider with limited scale
- Less mature ecosystem vs established providers
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Live GPU Pricing
Region Coverage
Popular Comparisons
Provider pages
Key differences
Cerebrium
Serverless ML deployment — H100, A100, T4 in seconds via custom containers
Lium
GPU marketplace — per-second billing, no minimum rental period