Chip comparison
NVIDIA GB200 Grace Blackwell Superchip vs NVIDIA V100 Tensor Core GPU
Side-by-side specs
Straight from each vendor's datasheet. Winner in bold: higher throughput, memory, or transistor count; lower power draw or price. Sparse (2:4) throughput roughly doubles the FP8/INT8 numbers shown.
| Field | NVIDIA GB200 Grace Blackwell Superchip | NVIDIA V100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC 4NP | TSMC 12FFN |
| Transistors (B) | — | 21.1 |
| Die size | — | 815 mm² |
| TDP | 2700 W | 300 W |
| Memory | 384 GB HBM3e | 32 GB HBM2 |
| Memory bandwidth | 16,000 GB/s | 900 GB/s |
| FP16 (dense) | — | 125 TFLOPS |
| FP8 (dense) | 9,000 TFLOPS | — |
| Form factor | Superchip (2xB200 + 1xGrace) | SXM2 / PCIe |
| Announced | 2024-03-18 | 2017-05-10 |
| Released | 2024-12-01 | 2017-12-01 |
Robots running NVIDIA GB200 Grace Blackwell Superchip
No robots publicly running it yet.
Robots running NVIDIA V100 Tensor Core GPU
No robots publicly running it yet.
Data centers with NVIDIA GB200 Grace Blackwell Superchip
Data centers with NVIDIA V100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
NVIDIA GB200 Grace Blackwell Superchip vs NVIDIA V100 Tensor Core GPU: which is faster for training?
NVIDIA GB200 Grace Blackwell Superchip has 72.00x the dense FP16/BF16 throughput of the other (NVIDIA GB200 Grace Blackwell Superchip: 9,000 TFLOPS; NVIDIA V100 Tensor Core GPU: 125 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
NVIDIA GB200 Grace Blackwell Superchip vs NVIDIA V100 Tensor Core GPU: which has more memory?
NVIDIA GB200 Grace Blackwell Superchip carries more HBM (NVIDIA GB200 Grace Blackwell Superchip: 384 GB HBM3e; NVIDIA V100 Tensor Core GPU: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
NVIDIA GB200 Grace Blackwell Superchip vs NVIDIA V100 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: NVIDIA GB200 Grace Blackwell Superchip 3.33 (9,000 ÷ 2700 W); NVIDIA V100 Tensor Core GPU 0.42 (125 ÷ 300 W). NVIDIA GB200 Grace Blackwell Superchip wins at the die level; system-level efficiency also depends on cooling and interconnect.
NVIDIA GB200 Grace Blackwell Superchip vs NVIDIA V100 Tensor Core GPU: which is more widely used?
NVIDIA GB200 Grace Blackwell Superchip: 0 robots and 11 data centers publicly running it. NVIDIA V100 Tensor Core GPU: 0 robots and 0 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · NVIDIA GB200 Grace Blackwell Superchip full page · NVIDIA V100 Tensor Core GPU full page.