PyTorch eager
Conv3d ReLU LeakyReLU GELU Sigmoid BiasAdd · depth = 32 · width = 64 · height = 64 · batch_size = 64 · in_channels = 8 · fp32 · run 01a03f0e-f6d2…
●passedReported evidence
Not re-observed recently.
Primary measurement
6.43ms±0.03 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 8.28 · min ms 6.4 · std ms 0.186 · mean ms 6.43
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 32 · width = 64 · height = 64 · batch_size = 64 · in_channels = 8 · fp32
comparison keysha256:fcbef96805404d6b…
sourceKernelBench baseline timings
external idH100_Modal/torch/level2/7_Conv3d_ReLU_LeakyReLU_GELU_Sigmoid_BiasAdd.py
sha256:9afa0e4579372bd6e9aff4e…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth32
width64
height64
batch_size64
in_channels8
input_1fp32 [64, 8, 32, 64, 64]
definition comparatornot_asserted
Measurements
latency · max8.28 ms · n=100
latency · mean6.43 ms · n=100
latency · min6.40 ms · n=100
latency · std186.0 µs
Protocol
harnessKernelBench timing scripts
timercuda_events
primaryStatisticmean
comparabilityFamilykernelbench_baseline_timing
Environment
gpuNVIDIA H100 (sm_90)
Artifacts
No artifacts published with this run.
Replications and notes
No attestations yet.
Community attestations. They never change the evidence level; only a KernelIndex-controlled rerun does.
Add a reproduction or note
Canonical manifest
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{
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"observedAt": "2026-03-05T08:38:15.000Z",
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}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Conv3d ReLU LeakyReLU GELU Sigmoid BiasAdd →JSON