Chip comparison
Google TPU v7 (Ironwood) vs NVIDIA H100 Tensor Core GPU
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) | NVIDIA H100 Tensor Core GPU |
|---|---|---|
| Process node | — | TSMC 4N |
| Transistors (B) | — | 80 |
| Die size | — | 814 mm² |
| TDP | 700 W | 700 W |
| Memory | 192 GB HBM3e | 80 GB HBM3 |
| Memory bandwidth | 7,400 GB/s | 3,350 GB/s |
| FP16 (dense) | — | 989 TFLOPS |
| BF16 (dense) | 4,614 TFLOPS | 989 TFLOPS |
| FP8 (dense) | 9,228 TFLOPS | 1,979 TFLOPS |
| INT8 (dense) | — | 1,979 TOPS |
| Launch price (list) | — | $30,000 |
| Form factor | OAM (Ironwood pod, up to 9,216 chips) | SXM5 |
| Announced | 2025-04-09 | 2022-03-22 |
| Released | 2025-12-01 | 2022-10-13 |
Robots running Google TPU v7 (Ironwood)
No robots publicly running it yet.
Robots running NVIDIA H100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Google TPU v7 (Ironwood)
No data centers publicly running it yet.
Common questions
Google TPU v7 (Ironwood) vs NVIDIA H100 Tensor Core GPU: which is faster for training?
Google TPU v7 (Ironwood) has 4.66x the dense FP8 throughput of the other (Google TPU v7 (Ironwood): 9,228 TFLOPS; NVIDIA H100 Tensor Core GPU: 1,979 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 NVIDIA H100 Tensor Core GPU: which has more memory?
Google TPU v7 (Ironwood) carries more HBM (Google TPU v7 (Ironwood): 192 GB HBM3e; NVIDIA H100 Tensor Core GPU: 80 GB HBM3). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Google TPU v7 (Ironwood) vs NVIDIA H100 Tensor Core GPU: which is more power-efficient?
Dense FP8 TFLOPS per watt: Google TPU v7 (Ironwood) 13.18 (9,228 ÷ 700 W); NVIDIA H100 Tensor Core GPU 2.83 (1,979 ÷ 700 W). Google TPU v7 (Ironwood) wins at the die level; system-level efficiency also depends on cooling and interconnect.
Google TPU v7 (Ironwood) vs NVIDIA H100 Tensor Core GPU: which is more widely used?
Google TPU v7 (Ironwood): 0 robots and 0 data centers publicly running it. NVIDIA H100 Tensor Core GPU: 0 robots and 7 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Google TPU v7 (Ironwood) full page · NVIDIA H100 Tensor Core GPU full page.