DEPLOYDatabase

Chip comparison

NVIDIA A10 Tensor Core GPU vs Tesla HW4 (FSD Computer 2)

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.

FieldNVIDIA A10 Tensor Core GPUTesla HW4 (FSD Computer 2)
Process nodeSamsung 8NSamsung 7LPP
Transistors (B)28.3
Die size628 mm²
TDP150 W90 W
Memory24 GB GDDR616 GB GDDR6
Memory bandwidth600 GB/s
FP16 (dense)125 TFLOPS
BF16 (dense)125 TFLOPS
INT8 (dense)250 TOPS300 TOPS
Form factorPCIeAuto-board (dual-SoC)
Announced2021-04-122023-01-01
Released2021-04-122023-02-01

Robots running NVIDIA A10 Tensor Core GPU

No robots publicly running it yet.

Robots running Tesla HW4 (FSD Computer 2)

Data centers with NVIDIA A10 Tensor Core GPU

No data centers publicly running it yet.

Data centers with Tesla HW4 (FSD Computer 2)

No data centers publicly running it yet.

Common questions

NVIDIA A10 Tensor Core GPU vs Tesla HW4 (FSD Computer 2): which has more memory?

NVIDIA A10 Tensor Core GPU carries more HBM (NVIDIA A10 Tensor Core GPU: 24 GB GDDR6; Tesla HW4 (FSD Computer 2): 16 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

NVIDIA A10 Tensor Core GPU vs Tesla HW4 (FSD Computer 2): which is more widely used?

NVIDIA A10 Tensor Core GPU: 0 robots and 0 data centers publicly running it. Tesla HW4 (FSD Computer 2): 3 robots and 0 data centers. Empty here means no operator has said publicly, not zero adoption in the market.

See also: every chip comparison · NVIDIA A10 Tensor Core GPU full page · Tesla HW4 (FSD Computer 2) full page.