Chip comparison
NVIDIA A100 Tensor Core GPU vs NVIDIA GB200 Grace Blackwell Superchip
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 A100 Tensor Core GPU | NVIDIA GB200 Grace Blackwell Superchip |
|---|---|---|
| Process node | TSMC N7 | TSMC 4NP |
| Transistors (B) | 54 | — |
| Die size | 826 mm² | — |
| TDP | 400 W | 2700 W |
| Memory | 80 GB HBM2e | 384 GB HBM3e |
| Memory bandwidth | 2,039 GB/s | 16,000 GB/s |
| FP16 (dense) | 312 TFLOPS | — |
| BF16 (dense) | 312 TFLOPS | — |
| FP8 (dense) | — | 9,000 TFLOPS |
| INT8 (dense) | 624 TOPS | — |
| Launch price (list) | $10,000 | — |
| Form factor | SXM4 | Superchip (2xB200 + 1xGrace) |
| Announced | 2020-05-14 | 2024-03-18 |
| Released | 2020-05-14 | 2024-12-01 |
Robots running NVIDIA A100 Tensor Core GPU
No robots publicly running it yet.
Robots running NVIDIA GB200 Grace Blackwell Superchip
No robots publicly running it yet.
Data centers with NVIDIA A100 Tensor Core GPU
No data centers publicly running it yet.
Data centers with NVIDIA GB200 Grace Blackwell Superchip
Common questions
NVIDIA A100 Tensor Core GPU vs NVIDIA GB200 Grace Blackwell Superchip: which is faster for training?
NVIDIA GB200 Grace Blackwell Superchip has 28.85x the dense FP16/BF16 throughput of the other (NVIDIA A100 Tensor Core GPU: 312 TFLOPS; NVIDIA GB200 Grace Blackwell Superchip: 9,000 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
NVIDIA A100 Tensor Core GPU vs NVIDIA GB200 Grace Blackwell Superchip: which has more memory?
NVIDIA GB200 Grace Blackwell Superchip carries more HBM (NVIDIA A100 Tensor Core GPU: 80 GB HBM2e; NVIDIA GB200 Grace Blackwell Superchip: 384 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
NVIDIA A100 Tensor Core GPU vs NVIDIA GB200 Grace Blackwell Superchip: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: NVIDIA A100 Tensor Core GPU 0.78 (312 ÷ 400 W); NVIDIA GB200 Grace Blackwell Superchip 3.33 (9,000 ÷ 2700 W). NVIDIA GB200 Grace Blackwell Superchip wins at the die level; system-level efficiency also depends on cooling and interconnect.
NVIDIA A100 Tensor Core GPU vs NVIDIA GB200 Grace Blackwell Superchip: which is more widely used?
NVIDIA A100 Tensor Core GPU: 0 robots and 0 data centers publicly running it. NVIDIA GB200 Grace Blackwell Superchip: 0 robots and 11 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · NVIDIA A100 Tensor Core GPU full page · NVIDIA GB200 Grace Blackwell Superchip full page.