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Chip comparison

Cambricon MLU370-X8 vs NVIDIA H200 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.

FieldCambricon MLU370-X8NVIDIA H200 Tensor Core GPU
Process nodeTSMC N7TSMC 4N
Transistors (B)80
Die size814 mm²
TDP250 W700 W
Memory48 GB LPDDR5141 GB HBM3e
Memory bandwidth4,800 GB/s
FP16 (dense)96 TFLOPS989 TFLOPS
BF16 (dense)989 TFLOPS
FP8 (dense)1,979 TFLOPS
INT8 (dense)256 TOPS1,979 TOPS
Form factorPCIeSXM5
Announced2022-03-252023-11-13
Released2024-03-01

Robots running Cambricon MLU370-X8

No robots publicly running it yet.

Robots running NVIDIA H200 Tensor Core GPU

No robots publicly running it yet.

Data centers with Cambricon MLU370-X8

No data centers publicly running it yet.

Common questions

Cambricon MLU370-X8 vs NVIDIA H200 Tensor Core GPU: which is faster for training?

NVIDIA H200 Tensor Core GPU has 20.61x the dense FP16/BF16 throughput of the other (Cambricon MLU370-X8: 96 TFLOPS; NVIDIA H200 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.

Cambricon MLU370-X8 vs NVIDIA H200 Tensor Core GPU: which has more memory?

NVIDIA H200 Tensor Core GPU carries more HBM (Cambricon MLU370-X8: 48 GB LPDDR5; NVIDIA H200 Tensor Core GPU: 141 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Cambricon MLU370-X8 vs NVIDIA H200 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Cambricon MLU370-X8 0.38 (96 ÷ 250 W); NVIDIA H200 Tensor Core GPU 2.83 (1,979 ÷ 700 W). NVIDIA H200 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.

Cambricon MLU370-X8 vs NVIDIA H200 Tensor Core GPU: which is more widely used?

Cambricon MLU370-X8: 0 robots and 0 data centers publicly running it. NVIDIA H200 Tensor Core GPU: 0 robots and 4 data centers. Empty here means no operator has said publicly, not zero adoption in the market.

See also: every chip comparison · Cambricon MLU370-X8 full page · NVIDIA H200 Tensor Core GPU full page.