Hardware caveat

Contents

Hardware caveat#

Every card records the device it was measured on: its name, compute capability or CPU model, and, for a GPU, the FP64 throughput and memory bandwidth the card’s ratios are taken against. The devices with a committed card are listed below; the lists are generated from the cards, so a device added next to them appears here without an edit.

GPUs#

device

compute capability / CPU model

date

NVIDIA H100 80GB HBM3

9.0

2026-10-13

NVIDIA L4

8.9

2026-10-14

NVIDIA A100-SXM4-40GB

8.0

2026-10-13

Tesla T4

7.5

2026-10-13

Quadro P2000

6.1

2026-10-13

NVIDIA RTX PRO 6000 Blackwell Server Edition

12.0

2026-10-14

device

driver

CUDA runtime

host CPU

Warp

JAX

PyTorch

CuPy

NVIDIA H100 80GB HBM3

580.178.04

12.9

Intel Xeon Platinum 8481C CPU @ 2.70GHz

1.17.0

0.11.2

2.12.1+cu129

14.2.0

NVIDIA L4

580.178.04

12.9

Intel Xeon CPU @ 2.20GHz

1.17.0

0.11.2

2.12.1+cu129

14.2.0

NVIDIA A100-SXM4-40GB

580.178.04

12.9

Intel Xeon CPU @ 2.20GHz

1.17.0

0.11.2

2.12.1+cu129

14.2.0

Tesla T4

580.178.04

12.9

Intel Xeon CPU @ 2.00GHz

1.17.0

0.11.2

2.12.1+cu129

14.2.0

Quadro P2000

560.35.03

12.9

Intel Xeon W-2125 CPU @ 4.00GHz

1.17.0

0.11.2

2.12.1

14.2.0

NVIDIA RTX PRO 6000 Blackwell Server Edition

580.178.04

12.9

AMD EPYC 9B45

1.17.0

0.11.2

2.12.1+cu129

14.2.0

CPUs#

device

compute capability / CPU model

date

AMD EPYC 9B45

AMD EPYC 9B45

2026-10-13

AMD EPYC 7B13

AMD EPYC 7B13

2026-10-13

Google Axion (Arm Neoverse-V2)

aarch64

2026-10-13

Intel Xeon Platinum 8581C

INTEL(R) XEON(R) PLATINUM 8581C CPU @ 2.30GHz

2026-10-13

device

driver

CUDA runtime

host CPU

Warp

JAX

PyTorch

CuPy

AMD EPYC 9B45

–

–

AMD EPYC 9B45

–

–

–

–

AMD EPYC 7B13

–

–

AMD EPYC 7B13

–

–

–

–

Google Axion (Arm Neoverse-V2)

–

–

aarch64

–

–

–

–

Intel Xeon Platinum 8581C

–

–

INTEL XEON PLATINUM 8581C CPU @ 2.30GHz

–

–

–

–

The method transfers to other hardware unchanged; the absolute numbers, and the crossover points between arms, differ from device to device, because FP64 throughput, memory bandwidth, launch overhead and core counts differ. Reading the numbers describes the NVIDIA H100 card and the AMD EPYC 9B45 card and names the device wherever it quotes another; each other device has its own tab on the results pages. A card from a new device is added beside these, produced by the same scripts.

One device is worth a note. The Tesla T4 (Kaggle, power-capped at 70 W) showed significant SM clock fluctuations between and within arm blocks, so its cells can move more from run to run; each card records the SM clock of every timed run.