Chip comparison
Mobileye EyeQ6 vs NVIDIA A10 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 A10 Tensor Core GPU |
|---|---|---|
| Process node | TSMC 7nm | Samsung 8N |
| Transistors (B) | — | 28.3 |
| Die size | — | 628 mm² |
| TDP | 33 W | 150 W |
| Memory | — | 24 GB GDDR6 |
| Memory bandwidth | — | 600 GB/s |
| FP16 (dense) | — | 125 TFLOPS |
| BF16 (dense) | — | 125 TFLOPS |
| INT8 (dense) | 34 TOPS | 250 TOPS |
| Form factor | Auto-safety SoC | PCIe |
| Announced | 2022-01-04 | 2021-04-12 |
| Released | 2024-01-01 | 2021-04-12 |
Robots running Mobileye EyeQ6
Robots running NVIDIA A10 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 A10 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Mobileye EyeQ6 vs NVIDIA A10 Tensor Core GPU: which is more widely used?
Mobileye EyeQ6: 1 robot and 0 data centers publicly running it. NVIDIA A10 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 A10 Tensor Core GPU full page.