DEPLOYDatabase

Chip comparison

Google TPU v7 (Ironwood) 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.

FieldGoogle TPU v7 (Ironwood)Tesla HW4 (FSD Computer 2)
Process nodeSamsung 7LPP
TDP700 W90 W
Memory192 GB HBM3e16 GB GDDR6
Memory bandwidth7,400 GB/s
BF16 (dense)4,614 TFLOPS
FP8 (dense)9,228 TFLOPS
INT8 (dense)300 TOPS
Form factorOAM (Ironwood pod, up to 9,216 chips)Auto-board (dual-SoC)
Announced2025-04-092023-01-01
Released2025-12-012023-02-01

Robots running Google TPU v7 (Ironwood)

No robots publicly running it yet.

Robots running Tesla HW4 (FSD Computer 2)

Data centers with Google TPU v7 (Ironwood)

No data centers publicly running it yet.

Data centers with Tesla HW4 (FSD Computer 2)

No data centers publicly running it yet.

Common questions

Google TPU v7 (Ironwood) vs Tesla HW4 (FSD Computer 2): which has more memory?

Google TPU v7 (Ironwood) carries more HBM (Google TPU v7 (Ironwood): 192 GB HBM3e; 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.

Google TPU v7 (Ironwood) vs Tesla HW4 (FSD Computer 2): which is more widely used?

Google TPU v7 (Ironwood): 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 · Google TPU v7 (Ironwood) full page · Tesla HW4 (FSD Computer 2) full page.