Chip comparison
Meta MTIA v2 vs NVIDIA V100 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 V100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N5 | TSMC 12FFN |
| Transistors (B) | — | 21.1 |
| Die size | — | 815 mm² |
| TDP | 90 W | 300 W |
| Memory | 128 GB LPDDR5 | 32 GB HBM2 |
| Memory bandwidth | 205 GB/s | 900 GB/s |
| FP16 (dense) | — | 125 TFLOPS |
| INT8 (dense) | 708 TOPS | — |
| Form factor | PCIe (internal Meta) | SXM2 / PCIe |
| Announced | 2024-04-10 | 2017-05-10 |
| Released | 2024-05-01 | 2017-12-01 |
Robots running Meta MTIA v2
No robots publicly running it yet.
Robots running NVIDIA V100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Meta MTIA v2
Data centers with NVIDIA V100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Meta MTIA v2 vs NVIDIA V100 Tensor Core GPU: which has more memory?
Meta MTIA v2 carries more HBM (Meta MTIA v2: 128 GB LPDDR5; NVIDIA V100 Tensor Core GPU: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Meta MTIA v2 vs NVIDIA V100 Tensor Core GPU: which is more widely used?
Meta MTIA v2: 0 robots and 2 data centers publicly running it. NVIDIA V100 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 V100 Tensor Core GPU full page.