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Chip comparison

Google TPU v7 (Ironwood) vs Intel Gaudi 3

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)Intel Gaudi 3
Process nodeTSMC N5
TDP700 W900 W
Memory192 GB HBM3e128 GB HBM2e
Memory bandwidth7,400 GB/s3,675 GB/s
FP16 (dense)1,835 TFLOPS
BF16 (dense)4,614 TFLOPS1,835 TFLOPS
FP8 (dense)9,228 TFLOPS1,835 TFLOPS
Form factorOAM (Ironwood pod, up to 9,216 chips)OAM
Announced2025-04-092024-04-09
Released2025-12-012024-09-01

Robots running Google TPU v7 (Ironwood)

No robots publicly running it yet.

Robots running Intel Gaudi 3

No robots publicly running it yet.

Data centers with Google TPU v7 (Ironwood)

No data centers publicly running it yet.

Data centers with Intel Gaudi 3

No data centers publicly running it yet.

Common questions

Google TPU v7 (Ironwood) vs Intel Gaudi 3: which is faster for training?

Google TPU v7 (Ironwood) has 5.03x the dense FP8 throughput of the other (Google TPU v7 (Ironwood): 9,228 TFLOPS; Intel Gaudi 3: 1,835 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

Google TPU v7 (Ironwood) vs Intel Gaudi 3: which has more memory?

Google TPU v7 (Ironwood) carries more HBM (Google TPU v7 (Ironwood): 192 GB HBM3e; Intel Gaudi 3: 128 GB HBM2e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Google TPU v7 (Ironwood) vs Intel Gaudi 3: which is more power-efficient?

Dense FP8 TFLOPS per watt: Google TPU v7 (Ironwood) 13.18 (9,228 ÷ 700 W); Intel Gaudi 3 2.04 (1,835 ÷ 900 W). Google TPU v7 (Ironwood) wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · Google TPU v7 (Ironwood) full page · Intel Gaudi 3 full page.