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Chip comparison

Meta MTIA v2 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.

FieldMeta MTIA v2NVIDIA A10 Tensor Core GPU
Process nodeTSMC N5Samsung 8N
Transistors (B)28.3
Die size628 mm²
TDP90 W150 W
Memory128 GB LPDDR524 GB GDDR6
Memory bandwidth205 GB/s600 GB/s
FP16 (dense)125 TFLOPS
BF16 (dense)125 TFLOPS
INT8 (dense)708 TOPS250 TOPS
Form factorPCIe (internal Meta)PCIe
Announced2024-04-102021-04-12
Released2024-05-012021-04-12

Robots running Meta MTIA v2

No robots publicly running it yet.

Robots running NVIDIA A10 Tensor Core GPU

No robots publicly running it yet.

Data centers with NVIDIA A10 Tensor Core GPU

No data centers publicly running it yet.

Common questions

Meta MTIA v2 vs NVIDIA A10 Tensor Core GPU: which has more memory?

Meta MTIA v2 carries more HBM (Meta MTIA v2: 128 GB LPDDR5; 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.

Meta MTIA v2 vs NVIDIA A10 Tensor Core GPU: which is more widely used?

Meta MTIA v2: 0 robots and 2 data centers publicly running it. NVIDIA A10 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 A10 Tensor Core GPU full page.