Chip comparison
NVIDIA B100 (Blackwell) 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 | NVIDIA B100 (Blackwell) | Tesla Dojo D1 |
|---|---|---|
| Process node | TSMC 4NP | TSMC N7 |
| Transistors (B) | — | 50 |
| Die size | — | 645 mm² |
| TDP | 700 W | 400 W |
| Memory | 192 GB HBM3e | — |
| Memory bandwidth | 8,000 GB/s | — |
| FP16 (dense) | 1,750 TFLOPS | — |
| BF16 (dense) | 1,750 TFLOPS | 362 TFLOPS |
| FP8 (dense) | 3,500 TFLOPS | 362 TFLOPS |
| Form factor | SXM6 (700 W envelope) | Training tile (25 D1 chips per tile) |
| Announced | 2024-03-18 | 2021-08-19 |
| Released | 2024-11-01 | 2023-07-01 |
Robots running NVIDIA B100 (Blackwell)
No robots publicly running it yet.
Robots running Tesla Dojo D1
No robots publicly running it yet.
Data centers with NVIDIA B100 (Blackwell)
No data centers publicly running it yet.
Data centers with Tesla Dojo D1
No data centers publicly running it yet.
Common questions
NVIDIA B100 (Blackwell) vs Tesla Dojo D1: which is faster for training?
NVIDIA B100 (Blackwell) has 9.67x the dense FP8 throughput of the other (NVIDIA B100 (Blackwell): 3,500 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.
NVIDIA B100 (Blackwell) vs Tesla Dojo D1: which is more power-efficient?
Dense FP8 TFLOPS per watt: NVIDIA B100 (Blackwell) 5.00 (3,500 ÷ 700 W); Tesla Dojo D1 0.91 (362 ÷ 400 W). NVIDIA B100 (Blackwell) wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · NVIDIA B100 (Blackwell) full page · Tesla Dojo D1 full page.