Chip comparison
Cerebras WSE-3 (Wafer-Scale Engine 3) 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 | Cerebras WSE-3 (Wafer-Scale Engine 3) | Tesla Dojo D1 |
|---|---|---|
| Process node | TSMC N5 | TSMC N7 |
| Transistors (B) | 4000 | 50 |
| Die size | 46225 mm² | 645 mm² |
| TDP | 23000 W | 400 W |
| Memory | 44 GB on-die SRAM | — |
| Memory bandwidth | 21,000,000 GB/s | — |
| FP16 (dense) | 62,500 TFLOPS | — |
| BF16 (dense) | — | 362 TFLOPS |
| FP8 (dense) | — | 362 TFLOPS |
| Form factor | wafer-scale (single-wafer system) | Training tile (25 D1 chips per tile) |
| Announced | 2024-03-13 | 2021-08-19 |
| Released | 2024-04-01 | 2023-07-01 |
Robots running Cerebras WSE-3 (Wafer-Scale Engine 3)
No robots publicly running it yet.
Robots running Tesla Dojo D1
No robots publicly running it yet.
Data centers with Cerebras WSE-3 (Wafer-Scale Engine 3)
No data centers publicly running it yet.
Data centers with Tesla Dojo D1
No data centers publicly running it yet.
Common questions
Cerebras WSE-3 (Wafer-Scale Engine 3) vs Tesla Dojo D1: which is faster for training?
Cerebras WSE-3 (Wafer-Scale Engine 3) has 172.65x the dense FP16/BF16 throughput of the other (Cerebras WSE-3 (Wafer-Scale Engine 3): 62,500 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.
Cerebras WSE-3 (Wafer-Scale Engine 3) vs Tesla Dojo D1: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Cerebras WSE-3 (Wafer-Scale Engine 3) 2.72 (62,500 ÷ 23000 W); Tesla Dojo D1 0.91 (362 ÷ 400 W). Cerebras WSE-3 (Wafer-Scale Engine 3) wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Cerebras WSE-3 (Wafer-Scale Engine 3) full page · Tesla Dojo D1 full page.