Chip comparison
NVIDIA T4 Tensor Core GPU 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 T4 Tensor Core GPU | Tesla Dojo D1 |
|---|---|---|
| Process node | TSMC 12FFN | TSMC N7 |
| Transistors (B) | 13.6 | 50 |
| Die size | 545 mm² | 645 mm² |
| TDP | 70 W | 400 W |
| Memory | 16 GB GDDR6 | — |
| Memory bandwidth | 320 GB/s | — |
| FP16 (dense) | 65 TFLOPS | — |
| BF16 (dense) | — | 362 TFLOPS |
| FP8 (dense) | — | 362 TFLOPS |
| INT8 (dense) | 130 TOPS | — |
| Form factor | PCIe (single-slot, low-profile) | Training tile (25 D1 chips per tile) |
| Announced | 2018-09-13 | 2021-08-19 |
| Released | 2019-01-01 | 2023-07-01 |
Robots running NVIDIA T4 Tensor Core GPU
No robots publicly running it yet.
Robots running Tesla Dojo D1
No robots publicly running it yet.
Data centers with NVIDIA T4 Tensor Core GPU
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Data centers with Tesla Dojo D1
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Common questions
NVIDIA T4 Tensor Core GPU vs Tesla Dojo D1: which is faster for training?
Tesla Dojo D1 has 5.57x the dense FP16/BF16 throughput of the other (NVIDIA T4 Tensor Core GPU: 65 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 T4 Tensor Core GPU vs Tesla Dojo D1: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W); Tesla Dojo D1 0.91 (362 ÷ 400 W). NVIDIA T4 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · NVIDIA T4 Tensor Core GPU full page · Tesla Dojo D1 full page.