Chip comparison
Mobileye EyeQ6 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 | Mobileye EyeQ6 | NVIDIA A100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC 7nm | TSMC N7 |
| Transistors (B) | — | 54 |
| Die size | — | 826 mm² |
| TDP | 33 W | 400 W |
| Memory | — | 80 GB HBM2e |
| Memory bandwidth | — | 2,039 GB/s |
| FP16 (dense) | — | 312 TFLOPS |
| BF16 (dense) | — | 312 TFLOPS |
| INT8 (dense) | 34 TOPS | 624 TOPS |
| Launch price (list) | — | $10,000 |
| Form factor | Auto-safety SoC | SXM4 |
| Announced | 2022-01-04 | 2020-05-14 |
| Released | 2024-01-01 | 2020-05-14 |
Robots running Mobileye EyeQ6
Robots running NVIDIA A100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Mobileye EyeQ6
No data centers publicly running it yet.
Data centers with NVIDIA A100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Mobileye EyeQ6 vs NVIDIA A100 Tensor Core GPU: which is more widely used?
Mobileye EyeQ6: 1 robot and 0 data centers 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 · Mobileye EyeQ6 full page · NVIDIA A100 Tensor Core GPU full page.