Chip comparison
Meta MTIA v2 vs NVIDIA A100 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 | Meta MTIA v2 | NVIDIA A100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N5 | TSMC N7 |
| Transistors (B) | — | 54 |
| Die size | — | 826 mm² |
| TDP | 90 W | 400 W |
| Memory | 128 GB LPDDR5 | 80 GB HBM2e |
| Memory bandwidth | 205 GB/s | 2,039 GB/s |
| FP16 (dense) | — | 312 TFLOPS |
| BF16 (dense) | — | 312 TFLOPS |
| INT8 (dense) | 708 TOPS | 624 TOPS |
| Launch price (list) | — | $10,000 |
| Form factor | PCIe (internal Meta) | SXM4 |
| Announced | 2024-04-10 | 2020-05-14 |
| Released | 2024-05-01 | 2020-05-14 |
Robots running Meta MTIA v2
No robots publicly running it yet.
Robots running NVIDIA A100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Meta MTIA v2
Data centers with NVIDIA A100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Meta MTIA v2 vs NVIDIA A100 Tensor Core GPU: which has more memory?
Meta MTIA v2 carries more HBM (Meta MTIA v2: 128 GB LPDDR5; NVIDIA A100 Tensor Core GPU: 80 GB HBM2e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Meta MTIA v2 vs NVIDIA A100 Tensor Core GPU: which is more widely used?
Meta MTIA v2: 0 robots and 2 data centers publicly running it. NVIDIA A100 Tensor Core GPU: 0 robots and 0 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Meta MTIA v2 full page · NVIDIA A100 Tensor Core GPU full page.