Chip comparison
Cambricon MLU370-X8 vs Tesla Dojo D1
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 | Cambricon MLU370-X8 | Tesla Dojo D1 |
|---|---|---|
| Process node | TSMC N7 | TSMC N7 |
| Transistors (B) | — | 50 |
| Die size | — | 645 mm² |
| TDP | 250 W | 400 W |
| Memory | 48 GB LPDDR5 | — |
| FP16 (dense) | 96 TFLOPS | — |
| BF16 (dense) | — | 362 TFLOPS |
| FP8 (dense) | — | 362 TFLOPS |
| INT8 (dense) | 256 TOPS | — |
| Form factor | PCIe | Training tile (25 D1 chips per tile) |
| Announced | 2022-03-25 | 2021-08-19 |
| Released | — | 2023-07-01 |
Robots running Cambricon MLU370-X8
No robots publicly running it yet.
Robots running Tesla Dojo D1
No robots publicly running it yet.
Data centers with Cambricon MLU370-X8
No data centers publicly running it yet.
Data centers with Tesla Dojo D1
No data centers publicly running it yet.
Common questions
Cambricon MLU370-X8 vs Tesla Dojo D1: which is faster for training?
Tesla Dojo D1 has 3.77x the dense FP16/BF16 throughput of the other (Cambricon MLU370-X8: 96 TFLOPS; Tesla Dojo D1: 362 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Cambricon MLU370-X8 vs Tesla Dojo D1: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Cambricon MLU370-X8 0.38 (96 ÷ 250 W); Tesla Dojo D1 0.91 (362 ÷ 400 W). Tesla Dojo D1 wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Cambricon MLU370-X8 full page · Tesla Dojo D1 full page.