torch.compile (inductor)
EfficientNetB1 · batch_size = 10 · fp32 · run 01a03f0e-f6ef…
●passedReported evidence
Not re-observed recently.
Primary measurement
2.19ms±0.01 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 2.32 · min ms 2.13 · std ms 0.0314 · mean ms 2.19
Identity
implementationtorch.compile (inductor)
projectPyTorch
revisionunknown
workloadbatch_size = 10 · fp32
comparison keysha256:4b1f474f916c0fc3…
sourceKernelBench baseline timings
external idH100_Modal/torch-compile-inductor/level3/23_EfficientNetB1.py
sha256:e9e1f0f98dd428f413801c1…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size10
input_1fp32 [10, 3, 240, 240]
definition comparatornot_asserted
Measurements
latency · max2.32 ms · n=100
latency · mean2.19 ms · n=100
latency · min2.13 ms · n=100
latency · std31.4 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": 2190000,
"maximum": 2320000,
"minimum": 2130000,
"confidence95": [
2183846,
2196154
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 31400,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 2.32,
"min_ms": 2.13,
"std_ms": 0.0314,
"mean_ms": 2.19
},
"benchmark": "H100_Modal/baseline_time_torch_compile_inductor_default.json",
"externalId": "H100_Modal/torch-compile-inductor/level3/23_EfficientNetB1.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:1985f9610f3bb47928884bf3cd32ad007058f883982a265d99a611ca4ffade83",
"environmentDigest": "sha256:2750ae381d6de582f1eb6b9008e0987463d19ede8af127d97d76c5ae09121393",
"implementationDigest": "sha256:a0b197522979086777c54e3230ecc7dbdc91c1d87d96e835d9cb1e24dee8cf7c"
},
"metadata": {
"name": "kernelbench-h100-modal-torch-compile-inductor-l3-23-efficientnetb1",
"title": "EfficientNetB1 · torch.compile (inductor) · Modal"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
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"repository": "https://github.com/ScalingIntelligence/KernelBench"
},
"measurement": {
"timer": "cuda_events",
"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"
},
"apiVersion": "kernelindex.dev/v1alpha1"
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"environment": {
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"spec": {
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"formFactor": "80GB HBM3",
"architecture": "sm_90"
},
"software": {}
},
"metadata": {
"name": "kernelbench-h100-modal",
"title": "KernelBench host · H100 80GB HBM3 (Modal)"
},
"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 EfficientNetB1 →JSON