DEPLOYDatabase

Chip comparison

NVIDIA B200 (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.

FieldNVIDIA B200 (Blackwell)Tesla Dojo D1
Process nodeTSMC 4NPTSMC N7
Transistors (B)20850
Die size645 mm²
TDP1000 W400 W
Memory192 GB HBM3e
Memory bandwidth8,000 GB/s
FP16 (dense)2,250 TFLOPS
BF16 (dense)2,250 TFLOPS362 TFLOPS
FP8 (dense)4,500 TFLOPS362 TFLOPS
INT8 (dense)4,500 TOPS
Form factorSXM6Training tile (25 D1 chips per tile)
Announced2024-03-182021-08-19
Released2024-11-012023-07-01

Robots running NVIDIA B200 (Blackwell)

No robots publicly running it yet.

Robots running Tesla Dojo D1

No robots publicly running it yet.

Data centers with Tesla Dojo D1

No data centers publicly running it yet.

Common questions

NVIDIA B200 (Blackwell) vs Tesla Dojo D1: which is faster for training?

NVIDIA B200 (Blackwell) has 12.43x the dense FP8 throughput of the other (NVIDIA B200 (Blackwell): 4,500 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 B200 (Blackwell) vs Tesla Dojo D1: which is more power-efficient?

Dense FP8 TFLOPS per watt: NVIDIA B200 (Blackwell) 4.50 (4,500 ÷ 1000 W); Tesla Dojo D1 0.91 (362 ÷ 400 W). NVIDIA B200 (Blackwell) wins at the die level; system-level efficiency also depends on cooling and interconnect.

NVIDIA B200 (Blackwell) vs Tesla Dojo D1: which is more widely used?

NVIDIA B200 (Blackwell): 0 robots and 3 data centers publicly running it. Tesla Dojo D1: 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 · NVIDIA B200 (Blackwell) full page · Tesla Dojo D1 full page.