Chip comparison
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA A10 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 A10 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N5 | Samsung 8N |
| Transistors (B) | 4000 | 28.3 |
| Die size | 46225 mm² | 628 mm² |
| TDP | 23000 W | 150 W |
| Memory | 44 GB on-die SRAM | 24 GB GDDR6 |
| Memory bandwidth | 21,000,000 GB/s | 600 GB/s |
| FP16 (dense) | 62,500 TFLOPS | 125 TFLOPS |
| BF16 (dense) | — | 125 TFLOPS |
| INT8 (dense) | — | 250 TOPS |
| Form factor | wafer-scale (single-wafer system) | PCIe |
| Announced | 2024-03-13 | 2021-04-12 |
| Released | 2024-04-01 | 2021-04-12 |
Robots running Cerebras WSE-3 (Wafer-Scale Engine 3)
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Robots running NVIDIA A10 Tensor Core GPU
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Data centers with Cerebras WSE-3 (Wafer-Scale Engine 3)
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Data centers with NVIDIA A10 Tensor Core GPU
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Common questions
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA A10 Tensor Core GPU: which is faster for training?
Cerebras WSE-3 (Wafer-Scale Engine 3) has 500.00x the dense FP16/BF16 throughput of the other (Cerebras WSE-3 (Wafer-Scale Engine 3): 62,500 TFLOPS; NVIDIA A10 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.
Cerebras WSE-3 (Wafer-Scale Engine 3) vs NVIDIA A10 Tensor Core GPU: which has more memory?
Cerebras WSE-3 (Wafer-Scale Engine 3) carries more HBM (Cerebras WSE-3 (Wafer-Scale Engine 3): 44 GB on-die SRAM; NVIDIA A10 Tensor Core GPU: 24 GB GDDR6). 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 A10 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 A10 Tensor Core GPU 0.83 (125 ÷ 150 W). Cerebras WSE-3 (Wafer-Scale Engine 3) wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Cerebras WSE-3 (Wafer-Scale Engine 3) full page · NVIDIA A10 Tensor Core GPU full page.