Chip comparison
Google TPU v5e vs NVIDIA B200 (Blackwell)
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 v5e | NVIDIA B200 (Blackwell) |
|---|---|---|
| Process node | — | TSMC 4NP |
| Transistors (B) | — | 208 |
| TDP | 170 W | 1000 W |
| Memory | 16 GB HBM2 | 192 GB HBM3e |
| Memory bandwidth | 819 GB/s | 8,000 GB/s |
| FP16 (dense) | — | 2,250 TFLOPS |
| BF16 (dense) | 197 TFLOPS | 2,250 TFLOPS |
| FP8 (dense) | — | 4,500 TFLOPS |
| INT8 (dense) | 393 TOPS | 4,500 TOPS |
| Form factor | OAM (v5e pod, up to 256 chips) | SXM6 |
| Announced | 2023-08-29 | 2024-03-18 |
| Released | 2023-11-01 | 2024-11-01 |
Robots running Google TPU v5e
No robots publicly running it yet.
Robots running NVIDIA B200 (Blackwell)
No robots publicly running it yet.
Data centers with Google TPU v5e
Data centers with NVIDIA B200 (Blackwell)
Common questions
Google TPU v5e vs NVIDIA B200 (Blackwell): which is faster for training?
NVIDIA B200 (Blackwell) has 22.84x the dense FP16/BF16 throughput of the other (Google TPU v5e: 197 TFLOPS; NVIDIA B200 (Blackwell): 4,500 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Google TPU v5e vs NVIDIA B200 (Blackwell): which has more memory?
NVIDIA B200 (Blackwell) carries more HBM (Google TPU v5e: 16 GB HBM2; NVIDIA B200 (Blackwell): 192 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Google TPU v5e vs NVIDIA B200 (Blackwell): which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Google TPU v5e 1.16 (197 ÷ 170 W); NVIDIA B200 (Blackwell) 4.50 (4,500 ÷ 1000 W). NVIDIA B200 (Blackwell) wins at the die level; system-level efficiency also depends on cooling and interconnect.
Google TPU v5e vs NVIDIA B200 (Blackwell): which is more widely used?
Google TPU v5e: 0 robots and 1 data center publicly running it. NVIDIA B200 (Blackwell): 0 robots and 3 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Google TPU v5e full page · NVIDIA B200 (Blackwell) full page.