Chip comparison
Google TPU v7 (Ironwood) 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 v7 (Ironwood) | Groq LPU (Language Processing Unit) |
|---|---|---|
| Process node | — | GlobalFoundries 14nm |
| TDP | 700 W | 375 W |
| Memory | 192 GB HBM3e | 0.23 GB SRAM (230 MB on-die) |
| Memory bandwidth | 7,400 GB/s | 80,000 GB/s |
| FP16 (dense) | — | 188 TFLOPS |
| BF16 (dense) | 4,614 TFLOPS | — |
| FP8 (dense) | 9,228 TFLOPS | — |
| INT8 (dense) | — | 750 TOPS |
| Form factor | OAM (Ironwood pod, up to 9,216 chips) | PCIe (GroqCard) / rack-scale GroqRack |
| Announced | 2025-04-09 | 2020-01-01 |
| Released | 2025-12-01 | 2021-06-01 |
Robots running Google TPU v7 (Ironwood)
No robots publicly running it yet.
Robots running Groq LPU (Language Processing Unit)
No robots publicly running it yet.
Data centers with Google TPU v7 (Ironwood)
No data centers publicly running it yet.
Data centers with Groq LPU (Language Processing Unit)
No data centers publicly running it yet.
Common questions
Google TPU v7 (Ironwood) vs Groq LPU (Language Processing Unit): which is faster for training?
Google TPU v7 (Ironwood) has 49.09x the dense FP16/BF16 throughput of the other (Google TPU v7 (Ironwood): 9,228 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 v7 (Ironwood) vs Groq LPU (Language Processing Unit): which has more memory?
Google TPU v7 (Ironwood) carries more HBM (Google TPU v7 (Ironwood): 192 GB HBM3e; 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 v7 (Ironwood) vs Groq LPU (Language Processing Unit): which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Google TPU v7 (Ironwood) 13.18 (9,228 ÷ 700 W); Groq LPU (Language Processing Unit) 0.50 (188 ÷ 375 W). Google TPU v7 (Ironwood) wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Google TPU v7 (Ironwood) full page · Groq LPU (Language Processing Unit) full page.