Chip comparison
Cambricon MLU370-X8 vs Google TPU v5e
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 | Cambricon MLU370-X8 | Google TPU v5e |
|---|---|---|
| Process node | TSMC N7 | — |
| TDP | 250 W | 170 W |
| Memory | 48 GB LPDDR5 | 16 GB HBM2 |
| Memory bandwidth | — | 819 GB/s |
| FP16 (dense) | 96 TFLOPS | — |
| BF16 (dense) | — | 197 TFLOPS |
| INT8 (dense) | 256 TOPS | 393 TOPS |
| Form factor | PCIe | OAM (v5e pod, up to 256 chips) |
| Announced | 2022-03-25 | 2023-08-29 |
| Released | — | 2023-11-01 |
Robots running Cambricon MLU370-X8
No robots publicly running it yet.
Robots running Google TPU v5e
No robots publicly running it yet.
Data centers with Cambricon MLU370-X8
No data centers publicly running it yet.
Data centers with Google TPU v5e
Common questions
Cambricon MLU370-X8 vs Google TPU v5e: which is faster for training?
Google TPU v5e has 2.05x the dense FP16/BF16 throughput of the other (Cambricon MLU370-X8: 96 TFLOPS; Google TPU v5e: 197 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Cambricon MLU370-X8 vs Google TPU v5e: which has more memory?
Cambricon MLU370-X8 carries more HBM (Cambricon MLU370-X8: 48 GB LPDDR5; Google TPU v5e: 16 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Cambricon MLU370-X8 vs Google TPU v5e: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Cambricon MLU370-X8 0.38 (96 ÷ 250 W); Google TPU v5e 1.16 (197 ÷ 170 W). Google TPU v5e wins at the die level; system-level efficiency also depends on cooling and interconnect.
Cambricon MLU370-X8 vs Google TPU v5e: which is more widely used?
Cambricon MLU370-X8: 0 robots and 0 data centers publicly running it. Google TPU v5e: 0 robots and 1 data center. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Cambricon MLU370-X8 full page · Google TPU v5e full page.