PyTorch eager
ConvTranspose3d Clamp Min Divide · depth = 24 · width = 48 · height = 48 · batch_size = 16 · in_channels = 64 · fp32 · run 01a03f0e-f83e…
●passedReported evidence
Not re-observed recently.
Primary measurement
20.6ms±0.02 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 20.8 · min ms 20.5 · std ms 0.0779 · mean ms 20.6
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddepth = 24 · width = 48 · height = 48 · batch_size = 16 · in_channels = 64 · fp32
comparison keysha256:4f352b27c0ccbeb0…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level2/100_ConvTranspose3d_Clamp_Min_Divide.py
sha256:51ca2fcf142fbdc554b1d1c…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
depth24
width48
height48
batch_size16
in_channels64
input_1fp32 [16, 64, 24, 48, 48]
definition comparatornot_asserted
Measurements
latency · max20.8 ms · n=100
latency · mean20.6 ms · n=100
latency · min20.5 ms · n=100
latency · std77.9 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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"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 ConvTranspose3d Clamp Min Divide →JSON