Chip comparison
Google TPU v5p vs NVIDIA V100 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 v5p | NVIDIA V100 Tensor Core GPU |
|---|---|---|
| Process node | — | TSMC 12FFN |
| Transistors (B) | — | 21.1 |
| Die size | — | 815 mm² |
| TDP | 300 W | 300 W |
| Memory | 95 GB HBM2e | 32 GB HBM2 |
| Memory bandwidth | 2,765 GB/s | 900 GB/s |
| FP16 (dense) | — | 125 TFLOPS |
| BF16 (dense) | 459 TFLOPS | — |
| INT8 (dense) | 918 TOPS | — |
| Form factor | OAM (per-chip in v5p pod) | SXM2 / PCIe |
| Announced | 2023-12-06 | 2017-05-10 |
| Released | 2024-01-01 | 2017-12-01 |
Robots running Google TPU v5p
No robots publicly running it yet.
Robots running NVIDIA V100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Google TPU v5p
Data centers with NVIDIA V100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Google TPU v5p vs NVIDIA V100 Tensor Core GPU: which is faster for training?
Google TPU v5p has 3.67x the dense FP16/BF16 throughput of the other (Google TPU v5p: 459 TFLOPS; NVIDIA V100 Tensor Core GPU: 125 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Google TPU v5p vs NVIDIA V100 Tensor Core GPU: which has more memory?
Google TPU v5p carries more HBM (Google TPU v5p: 95 GB HBM2e; NVIDIA V100 Tensor Core GPU: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Google TPU v5p vs NVIDIA V100 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Google TPU v5p 1.53 (459 ÷ 300 W); NVIDIA V100 Tensor Core GPU 0.42 (125 ÷ 300 W). Google TPU v5p wins at the die level; system-level efficiency also depends on cooling and interconnect.
Google TPU v5p vs NVIDIA V100 Tensor Core GPU: which is more widely used?
Google TPU v5p: 0 robots and 1 data center publicly running it. NVIDIA V100 Tensor Core GPU: 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 v5p full page · NVIDIA V100 Tensor Core GPU full page.