H100 Specifications
Fourth-generation Tensor Cores speed up all precisions, including FP64, TF32, FP32, FP16, INT8, and FP8, to reduce memory usage and increase performance while still maintaining accuracy for LLMs.
80 GB
HBM3 Memory
Run 70B+ parameter models on a single GPU.
900 GB/s
NVLink Bandwidth
Fourth-gen NVLink for multi-GPU scaling.
1,979
TFLOPS FP16
3,958 TFLOPS at FP8 with Transformer Engine.
9X
Faster Pre-Training
vs A100 on large language models.
NVIDIA B200 on Denvr AI Cloud
1T Parameter Training
Scale across 8-GPU NVLink nodes for 1,440 GB of total VRAM and 1.8 TB/s per-GPU interconnect.
LLM Inference
Serve 70B+ parameter models on a single GPU, or scale to 8 GPUs with 640 GB VRAM for 500B+ parameter models at FP8 precision.
Production AI
H100 delivers 9x faster training vs. A100 at $2.10/hr on-demand. For extended context or larger models, consider the H200 with 141 GB HBM3e.
Managed Storage
High-performance Weka filesystem and local NVMe available. No external storage to provision for datasets, checkpoints, or model artifacts.
Configurations
Per-minute billing with on-demand and reserved options. All configurations available as bare metal, VM, or model endpoints.
Platform
GPUs
On-Demand
VRAM
vCPUs
Memory
Local Storage
Interconnect
NVIDIA H100 SXM
8
80 GB
208
1024 GB
6x 3.8TB NVMe
IB 3200G
$2.30 / GPU