Chip comparison
Google TPU v6 (Trillium) vs Groq LPU (Language Processing Unit)
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 | Google TPU v6 (Trillium) | Groq LPU (Language Processing Unit) |
|---|---|---|
| Process node | — | GlobalFoundries 14nm |
| TDP | 200 W | 375 W |
| Memory | 32 GB HBM3 | 0.23 GB SRAM (230 MB on-die) |
| Memory bandwidth | 1,600 GB/s | 80,000 GB/s |
| FP16 (dense) | — | 188 TFLOPS |
| BF16 (dense) | 918 TFLOPS | — |
| FP8 (dense) | 1,836 TFLOPS | — |
| INT8 (dense) | 1,836 TOPS | 750 TOPS |
| Form factor | OAM (Trillium pod, up to 256 chips) | PCIe (GroqCard) / rack-scale GroqRack |
| Announced | 2024-05-14 | 2020-01-01 |
| Released | 2024-12-01 | 2021-06-01 |
Robots running Google TPU v6 (Trillium)
No robots publicly running it yet.
Robots running Groq LPU (Language Processing Unit)
No robots publicly running it yet.
Data centers with Google TPU v6 (Trillium)
Data centers with Groq LPU (Language Processing Unit)
No data centers publicly running it yet.
Common questions
Google TPU v6 (Trillium) vs Groq LPU (Language Processing Unit): which is faster for training?
Google TPU v6 (Trillium) has 9.77x the dense FP16/BF16 throughput of the other (Google TPU v6 (Trillium): 1,836 TFLOPS; Groq LPU (Language Processing Unit): 188 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Google TPU v6 (Trillium) vs Groq LPU (Language Processing Unit): which has more memory?
Google TPU v6 (Trillium) carries more HBM (Google TPU v6 (Trillium): 32 GB HBM3; Groq LPU (Language Processing Unit): 0.23 GB SRAM (230 MB on-die)). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Google TPU v6 (Trillium) vs Groq LPU (Language Processing Unit): which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Google TPU v6 (Trillium) 9.18 (1,836 ÷ 200 W); Groq LPU (Language Processing Unit) 0.50 (188 ÷ 375 W). Google TPU v6 (Trillium) wins at the die level; system-level efficiency also depends on cooling and interconnect.
Google TPU v6 (Trillium) vs Groq LPU (Language Processing Unit): which is more widely used?
Google TPU v6 (Trillium): 0 robots and 1 data center publicly running it. Groq LPU (Language Processing Unit): 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 · Google TPU v6 (Trillium) full page · Groq LPU (Language Processing Unit) full page.