Chip comparison
Mobileye EyeQ6 vs NVIDIA H100 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 H100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC 7nm | TSMC 4N |
| Transistors (B) | — | 80 |
| Die size | — | 814 mm² |
| TDP | 33 W | 700 W |
| Memory | — | 80 GB HBM3 |
| Memory bandwidth | — | 3,350 GB/s |
| FP16 (dense) | — | 989 TFLOPS |
| BF16 (dense) | — | 989 TFLOPS |
| FP8 (dense) | — | 1,979 TFLOPS |
| INT8 (dense) | 34 TOPS | 1,979 TOPS |
| Launch price (list) | — | $30,000 |
| Form factor | Auto-safety SoC | SXM5 |
| Announced | 2022-01-04 | 2022-03-22 |
| Released | 2024-01-01 | 2022-10-13 |
Robots running Mobileye EyeQ6
Robots running NVIDIA H100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Mobileye EyeQ6
No data centers publicly running it yet.
Common questions
Mobileye EyeQ6 vs NVIDIA H100 Tensor Core GPU: which is more widely used?
Mobileye EyeQ6: 1 robot and 0 data centers publicly running it. NVIDIA H100 Tensor Core GPU: 0 robots and 7 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 H100 Tensor Core GPU full page.