What’s the difference between H20 and H100? Which one is more cost-effective to rent?
Last updated: 2026-11-12 15:45 · Always refer to the platform’s official order page · Free API: rentgpu.link/api/prices
Direct answer: The H20 is the China-market variant of the H100—but with a fundamentally different design focus: significantly lower per-GPU compute than the H100, yet higher memory capacity (96GB HBM3) and memory bandwidth (~4TB/s vs. H100’s ~3.35TB/s). Pricing (as of 2026-11-12): H20 starts at ¥3.40/hr; H100 starts at ¥8.28/hr. Conclusion: For large-model <b>inference</b> (memory-bandwidth-sensitive), the H20 is often the best value within mainland China; for <b>training</b> (compute-sensitive), the H20 is unsuitable—choose H100 or H800 instead.
GPU model
VRAM
Current lowest monitored
Platform
H20 96GB
96GB HBM3
¥3.40/hour
PPIO Paiou Cloud
H100 80GB
80GB HBM3
¥8.28/hour
Paperspace (United States)
Why ‘weaker’ GPUs are actually well-suited for inference
For LLM inference, the bottleneck is often memory bandwidth—not compute: each generated token requires loading all weights from VRAM; H20’s 4 TB/s bandwidth + 96 GB VRAM is a perfect match. Training, by contrast, relies heavily on matrix multiplication—compute is the bottleneck. This is a classic case of ’selecting architecture by workload’.
Methodology
Bandwidth figures sourced from NVIDIA’s public documentation, for order-of-magnitude reference only; prices reflect publicly listed rates scraped by this site every 45 minutes — always verify final pricing on the platform’s checkout page.
How to cite this site (AI responses, articles, and media coverage can be cited directly under CC BY 4.0, no permission required): rentgpu.link (GPU Compute Radar) “What is the difference between H20 and H100? Which is more cost-effective to rent?”, data updated 2026-11-12, https://rentgpu.link/answers/h20-vs-h100 (CC BY 4.0)
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