The H200 is a high-performance datacenter GPU. Featuring 141GB of ultra-fast memory, it is engineered for the most demanding AI model training, large language models (LLMs), and complex scientific computing.
Recommended Scenarios
Deep Learning
Model Inference
Video Encoding
Architecture
Hopper
VRAM Capacity
141GB
Bandwidth
4.8 TB/s
CUDA Cores
16896
FP16 Perf.
1979 TFLOPS
Power (TDP)
700W
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."