torch.compile (inductor)
MobileNetV1 · width = 224 · height = 224 · batch_size = 10 · input_channels = 3 · fp32 · run 01a03f0e-f853…
●passedReported evidence
Not re-observed recently.
Primary measurement
3.35ms±0.02 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 4.22 · min ms 3.26 · std ms 0.101 · mean ms 3.35
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadwidth = 224 · height = 224 · batch_size = 10 · input_channels = 3 · fp32
comparison keysha256:e48b2e179d6e1069…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch-compile-inductor/level3/19_MobileNetV1.py
sha256:06a687976c61ad5d52478b4…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
width224
height224
batch_size10
input_channels3
input_1fp32 [10, 3, 224, 224]
definition comparatornot_asserted
Measurements
latency · max4.22 ms · n=100
latency · mean3.35 ms · n=100
latency · min3.26 ms · n=100
latency · std101.0 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": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 3350000,
"maximum": 4220000,
"minimum": 3260000,
"confidence95": [
3330204,
3369796
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 101000,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
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"metrics": {
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"min_ms": 3.26,
"std_ms": 0.101,
"mean_ms": 3.35
},
"benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch_compile_inductor_default.json",
"externalId": "H100_PCIe_LambdaLabs/torch-compile-inductor/level3/19_MobileNetV1.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:00996d9be006d45ff397db32ee5299c5fc946a80d8168f53bbb7015a6ac62b45",
"environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
"implementationDigest": "sha256:70ea2f7bc18e53af8b4fe96b1ef8c694d864308a3fc0362d553c0507ed0f3fe2"
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs-torch-compile-inductor-l3-19-mobilenetv1",
"title": "MobileNetV1 · torch.compile (inductor) · Lambda Labs"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
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"repository": "https://github.com/ScalingIntelligence/KernelBench"
},
"measurement": {
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"primaryStatistic": "mean"
},
"comparability": {
"notes": "Mean of 100 timed forward passes (CUDA events, warm-up excluded) of the reference module on fixed inputs; the 95% interval is the mean's, from the reported standard deviation. The upstream JSON records no torch or CUDA version. Comparable only within one problem and one timing host.",
"family": "kernelbench_baseline_timing"
}
},
"metadata": {
"name": "kernelbench-timing-v1",
"title": "KernelBench baseline timing"
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"environment": {
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"title": "KernelBench host · H100 PCIe (Lambda Labs)"
},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}Cite this record (permalink, digest, access date)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for MobileNetV1 →JSON