Contents
- H100 Specs
- Paperspace H100 Pricing
- How to Rent
- Comparison with Alternatives
- Performance Benchmarks
- FAQ
- Related Resources
- Sources
H100 Specs
- 80GB HBM3 memory
- 3.35 TB/s bandwidth (SXM), 2 TB/s (PCIe)
- FP32: 67 TFLOPS
- TF32: 661 TFLOPS
- FP8: 3,958 TFLOPS
See H100 specs guide for details.
Paperspace H100 Pricing
Paperspace offers H100 access through its cloud GPU platform. As of March 2026, exact pricing varies based on machine configuration and region. Standard H100 instances run between $2.50 and $3.00 per hour depending on the exact specification and data center location.
Pricing breakdown by variant:
- H100 PCIe: Typically $2.50-2.80/hour
- H100 SXM: Typically $2.80-3.20/hour
Paperspace bundles storage, bandwidth, and compute into monthly plans. Users pay for active machine time, with hourly rates applied to any running instance. The platform offers both on-demand and pre-reserved capacity options.
For comparative pricing analysis, explore RunPod GPU pricing and Lambda GPU pricing to understand the full market.
How to Rent
- Sign up at paperspace.com
- Select H100 from GPU dropdown
- Pick region and config
- Launch instance
- SSH or Jupyter in
Pre-installed: PyTorch, TensorFlow, Jupyter. Good for fine-tuning, inference, training.
Comparison with Alternatives
Multiple providers offer H100 access. Each platform has distinct pricing models and feature sets.
| Provider | H100 PCIe | H100 SXM | Key Strength |
|---|---|---|---|
| Paperspace | $2.50-2.80/hr | $2.80-3.20/hr | User-friendly interface |
| RunPod | $1.99/hr | $2.69/hr | Lowest prices |
| Lambda | $2.86/hr | $3.78/hr | production support |
| CoreWeave | $49.24 (8x) | N/A | Bulk pricing |
Paperspace positions itself for users prioritizing ease-of-use over lowest cost. The platform handles networking, storage, and scaling automatically, reducing operational complexity.
Performance Benchmarks
H100 performance varies by workload type. For LLM inference, a single H100 serves approximately 500-800 tokens per second depending on model size and batch size.
Training benchmarks show:
- 7B parameter models: 1,200-1,400 tokens/sec
- 13B parameter models: 900-1,100 tokens/sec
- 70B parameter models: 250-400 tokens/sec
These metrics depend heavily on precision (FP32, TF32, or FP8), batch size, and sequence length. Mixed precision training yields substantial speedups over full FP32 approaches.
Memory efficiency varies by framework. PyTorch with gradient checkpointing reduces memory usage by 30-40% at the cost of modest compute overhead.
FAQ
How much does the H100 cost on Paperspace per month? A 24/7 running H100 PCIe instance costs approximately $1,800-2,000 monthly. Typical users run intermittent workloads, so actual costs fall lower.
Can I use a single H100 for multi-user inference? Yes, with careful batching and request queuing, one H100 handles 10-20 concurrent users depending on model size.
Does Paperspace offer reserved instances? Yes, discounts apply to pre-reserved monthly or annual commitments.
What operating systems does Paperspace support? Ubuntu Linux is standard. Windows is available but less common for ML workloads.
How is data transfer charged? Paperspace charges for outbound data transfer. Inbound typically runs free or at reduced rates.
Related Resources
Sources
- NVIDIA H100 Tensor GPU Specifications (official NVIDIA documentation)
- Paperspace Cloud GPU Pricing Documentation
- MLPerf Benchmarks for GPU Accelerators