AI Insights
The NVIDIA H200 is the first GPU to feature HBM3e, delivering 141GB of memory at 4.8TB/s. This allows for significantly larger models to be held in a single GPU’s memory, reducing the complexity of multi-GPU orchestration. It is particularly effective for high-throughput LLM inference. We track H200 availability across leading cloud providers to help you secure this cutting-edge hardware.
The H200 is a high-performance Inferred GPU.
Recommended Scenarios
Deep Learning
Model Inference
Video Encoding
Architecture
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What Users Say
Real experiences from ML engineers and researchers
Long-context LLM inferenceTwitter
"Just got access to H200s. The 141GB HBM3e is wild — we can now run 70B models with 32k context length in FP16 without offloading. Previously needed 2xH100s for that. Single-GPU simplicity is worth the premium for inference workloads. Still rare though, only a few providers have them."
Benchmarking various workloadsReddit
"H200 is basically an H100 with more memory and faster memory bandwidth. If your workload is compute-bound (most training), it's barely faster. But if you're memory-bound (big context windows, large batch inference), the difference is massive. Know your bottleneck before paying 2x the price."
Client consulting projectHacker News
"We paid $4.50/hr for H200s because we needed the memory for a specific client project. Results were great but honestly? Most of the time 2xH100s would've been cheaper and faster. H200s only make sense if you absolutely need that single-GPU memory capacity. They're niche, not a default choice."