Chip comparison
AMD Instinct MI350 series vs NVIDIA A100 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 | AMD Instinct MI350 series | NVIDIA A100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N3 (chiplet) | TSMC N7 |
| Transistors (B) | — | 54 |
| Die size | — | 826 mm² |
| TDP | 1000 W | 400 W |
| Memory | 288 GB HBM3e | 80 GB HBM2e |
| Memory bandwidth | 8,000 GB/s | 2,039 GB/s |
| FP16 (dense) | 2,300 TFLOPS | 312 TFLOPS |
| BF16 (dense) | 2,300 TFLOPS | 312 TFLOPS |
| FP8 (dense) | 4,600 TFLOPS | — |
| INT8 (dense) | 4,600 TOPS | 624 TOPS |
| Launch price (list) | — | $10,000 |
| Form factor | OAM | SXM4 |
| Announced | 2025-06-12 | 2020-05-14 |
| Released | 2025-10-01 | 2020-05-14 |
Robots running AMD Instinct MI350 series
No robots publicly running it yet.
Robots running NVIDIA A100 Tensor Core GPU
No robots publicly running it yet.
Data centers with AMD Instinct MI350 series
Data centers with NVIDIA A100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
AMD Instinct MI350 series vs NVIDIA A100 Tensor Core GPU: which is faster for training?
AMD Instinct MI350 series has 14.74x the dense FP16/BF16 throughput of the other (AMD Instinct MI350 series: 4,600 TFLOPS; NVIDIA A100 Tensor Core GPU: 312 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
AMD Instinct MI350 series vs NVIDIA A100 Tensor Core GPU: which has more memory?
AMD Instinct MI350 series carries more HBM (AMD Instinct MI350 series: 288 GB HBM3e; NVIDIA A100 Tensor Core GPU: 80 GB HBM2e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AMD Instinct MI350 series vs NVIDIA A100 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AMD Instinct MI350 series 4.60 (4,600 ÷ 1000 W); NVIDIA A100 Tensor Core GPU 0.78 (312 ÷ 400 W). AMD Instinct MI350 series wins at the die level; system-level efficiency also depends on cooling and interconnect.
AMD Instinct MI350 series vs NVIDIA A100 Tensor Core GPU: which is more widely used?
AMD Instinct MI350 series: 0 robots and 1 data center publicly running it. NVIDIA A100 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 · AMD Instinct MI350 series full page · NVIDIA A100 Tensor Core GPU full page.