PyTorch eager
4D tensor matrix multiplication · b = 8 · i = 256 · j = 512 · k = 768 · l = 256 · fp32 · run 01a03f0e-f830…
●passedReported evidence
Not re-observed recently.
Primary measurement
12.6ms±0.11 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 13.6 · min ms 11.3 · std ms 0.557 · mean ms 12.6
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadb = 8 · i = 256 · j = 512 · k = 768 · l = 256 · fp32
comparison keysha256:03b81849e1401a04…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/11_4D_tensor_matrix_multiplication.py
sha256:7b78c4a4c09f15f8bf58586…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
b8
i256
j512
k768
l256
afp32 [8, 256, 512, 256]
bfp32 [256, 768]
definition comparatornot_asserted
Measurements
latency · max13.6 ms · n=100
latency · mean12.6 ms · n=100
latency · min11.3 ms · n=100
latency · std557.0 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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{
"run": {
"kind": "BenchmarkRun",
"spec": {
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"timing": {
"samples": 100,
"latencyNs": {
"mean": 12600000,
"maximum": 13600000,
"minimum": 11300000,
"confidence95": [
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]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 557000,
"metric": "latency",
"statistic": "std"
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"sourceNative": {
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},
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"metadata": {
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},
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"comparability": {
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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 4D tensor matrix multiplication →JSON