Chip comparison
Groq LPU (Language Processing Unit) 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 | Groq LPU (Language Processing Unit) | Tesla Dojo D1 |
|---|---|---|
| Process node | GlobalFoundries 14nm | TSMC N7 |
| Transistors (B) | — | 50 |
| Die size | — | 645 mm² |
| TDP | 375 W | 400 W |
| Memory | 0.23 GB SRAM (230 MB on-die) | — |
| Memory bandwidth | 80,000 GB/s | — |
| FP16 (dense) | 188 TFLOPS | — |
| BF16 (dense) | — | 362 TFLOPS |
| FP8 (dense) | — | 362 TFLOPS |
| INT8 (dense) | 750 TOPS | — |
| Form factor | PCIe (GroqCard) / rack-scale GroqRack | Training tile (25 D1 chips per tile) |
| Announced | 2020-01-01 | 2021-08-19 |
| Released | 2021-06-01 | 2023-07-01 |
Robots running Groq LPU (Language Processing Unit)
No robots publicly running it yet.
Robots running Tesla Dojo D1
No robots publicly running it yet.
Data centers with Groq LPU (Language Processing Unit)
No data centers publicly running it yet.
Data centers with Tesla Dojo D1
No data centers publicly running it yet.
Common questions
Groq LPU (Language Processing Unit) vs Tesla Dojo D1: which is faster for training?
Tesla Dojo D1 has 1.93x the dense FP16/BF16 throughput of the other (Groq LPU (Language Processing Unit): 188 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.
Groq LPU (Language Processing Unit) vs Tesla Dojo D1: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Groq LPU (Language Processing Unit) 0.50 (188 ÷ 375 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 · Groq LPU (Language Processing Unit) full page · Tesla Dojo D1 full page.