Chip comparison
Mobileye EyeQ6 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 | Mobileye EyeQ6 | NVIDIA V100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC 7nm | TSMC 12FFN |
| Transistors (B) | — | 21.1 |
| Die size | — | 815 mm² |
| TDP | 33 W | 300 W |
| Memory | — | 32 GB HBM2 |
| Memory bandwidth | — | 900 GB/s |
| FP16 (dense) | — | 125 TFLOPS |
| INT8 (dense) | 34 TOPS | — |
| Form factor | Auto-safety SoC | SXM2 / PCIe |
| Announced | 2022-01-04 | 2017-05-10 |
| Released | 2024-01-01 | 2017-12-01 |
Robots running Mobileye EyeQ6
Robots running NVIDIA V100 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 V100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Mobileye EyeQ6 vs NVIDIA V100 Tensor Core GPU: which is more widely used?
Mobileye EyeQ6: 1 robot and 0 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 · Mobileye EyeQ6 full page · NVIDIA V100 Tensor Core GPU full page.