NVIDIA GH200 Grace Hopper vs NVIDIA GB200 (Grace Blackwell 200, 2024-Q4): Spec Comparison & Buyer's Guide
In AI infrastructure selection, NVIDIA GH200 Grace Hopper and NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) are two accelerators frequently compared. This article contrasts them item by item — architecture, compute, memory, power, and release cadence — to help you quickly judge which fits training or inference workloads.
Spec Comparison Table
| Vendor | NVIDIA GH200 Grace Hopper | NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) |
|---|---|---|
| Vendor | NVIDIA | NVIDIA |
| Architecture | Grace+ Hopper | Grace Blackwell 200 Superchip |
| Process | TSMC 4nm | — |
| Release Date | 2023 ,2024 | 2024-03-18 |
| FP8 Compute | 3,958 TFLOPS | — |
| FP16 Compute | 1,979 TFLOPS | — |
| FP32 Compute | 134 TFLOPS | — |
| INT8 Compute | 3,958 TOPS | — |
| Memory Type | HBM3 | — |
| Memory Capacity | 96 GB HBM3 | — |
| Memory Bandwidth | 4.8 TB/s/ 6.35 TB/s | — |
| TDP Power | 1000 W | 1000W |
Key Differences
- The two chips are positioned similarly; evaluate based on your specific workload, software-stack maturity, and supply-chain availability.
Selection Advice
- When chasing extreme single-card compute and a mature toolchain, prioritize NVIDIA GH200 Grace Hopper; if budget, power wall, or local support are hard constraints, NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) often fits better. Use this site's AI Compute Card Comparison Tool to validate multiple chips side-by-side before deciding.
FAQ
What are the main differences between NVIDIA GH200 Grace Hopper and NVIDIA GB200 (Grace Blackwell 200, 2024-Q4)?
The core difference is architecture and compute density: NVIDIA GH200 Grace Hopper uses Grace+ Hopper, FP8 ~3,958 TFLOPS, memory 96 GB HBM3; NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) uses Grace Blackwell 200 Superchip, FP8 ~No public FP8 data, memory —. See the comparison table above.
What is the TDP (power) of NVIDIA GH200 Grace Hopper?
NVIDIA GH200 Grace Hopper has a TDP of 1000 W; actual whole-system power also includes board, fans, and PUE.
Which is better for large-model training / inference?
Training values memory capacity, bandwidth, and multi-card interconnect; inference values single-card throughput and power efficiency. Combine the "Key Differences" and "Selection Advice" above with your batch size, model size, and SLA.
How much do NVIDIA GH200 Grace Hopper and NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) differ in memory capacity?
NVIDIA GH200 Grace Hopper is 96 GB HBM3, NVIDIA GB200 (Grace Blackwell 200, 2024-Q4) is —; the gap directly affects loadable model size and context length.
Related Pages
- NVIDIA GH200 Grace Hopper
- NVIDIA GB200 (Grace Blackwell 200, 2024-Q4)
- AI 算力卡对比工具 — Compare 2–4 chips side-by-side online