Chip comparison
Cerebras WSE-3 (Wafer-Scale Engine 3) 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.
| Field | Cerebras WSE-3 (Wafer-Scale Engine 3) | NVIDIA H200 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N5 | TSMC 4N |
| Transistors (B) | 4000 | 80 |
| Die size | 46225 mm² | 814 mm² |
| TDP | 23000 W | 700 W |
| Memory | 44 GB on-die SRAM | 141 GB HBM3e |
| Memory bandwidth | 21,000,000 GB/s | 4,800 GB/s |
| FP16 (dense) | 62,500 TFLOPS | 989 TFLOPS |
| BF16 (dense) | — | 989 TFLOPS |
| FP8 (dense) | — | 1,979 TFLOPS |
| INT8 (dense) | — | 1,979 TOPS |
| Form factor | wafer-scale (single-wafer system) | SXM5 |
| Announced | 2024-03-13 | 2023-11-13 |
| Released | 2024-04-01 | 2024-03-01 |
Robots running Cerebras WSE-3 (Wafer-Scale Engine 3)
No robots publicly running it yet.
Robots running NVIDIA H200 Tensor Core GPU
No robots publicly running it yet.
Data centers with Cerebras WSE-3 (Wafer-Scale Engine 3)
No data centers publicly running it yet.
Data centers with NVIDIA H200 Tensor Core GPU
Common questions
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA H200 Tensor Core GPU: which is faster for training?
Cerebras WSE-3 (Wafer-Scale Engine 3) has 31.58x the dense FP16/BF16 throughput of the other (Cerebras WSE-3 (Wafer-Scale Engine 3): 62,500 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.
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA H200 Tensor Core GPU: which has more memory?
NVIDIA H200 Tensor Core GPU carries more HBM (Cerebras WSE-3 (Wafer-Scale Engine 3): 44 GB on-die SRAM; 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.
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA H200 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Cerebras WSE-3 (Wafer-Scale Engine 3) 2.72 (62,500 ÷ 23000 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.
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA H200 Tensor Core GPU: which is more widely used?
Cerebras WSE-3 (Wafer-Scale Engine 3): 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 · Cerebras WSE-3 (Wafer-Scale Engine 3) full page · NVIDIA H200 Tensor Core GPU full page.