PyTorch eager
HuberLoss · batch_size = 32768 · fp32 · run 01a03f0e-f837…
●passedReported evidence
Not re-observed recently.
Primary measurement
9.00ms±0.00 · mean of 100
Rank 2 in its comparison group · source-native comparison · observed 2026-03-05
max ms 9.05 · min ms 8.99 · std ms 0.00792 · mean ms 9
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloadbatch_size = 32768 · fp32
comparison keysha256:05372593bcff5dc4…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/96_HuberLoss.py
sha256:2e8b1e9d24bc19486ca0810…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
batch_size32768
input_2fp32 [32768, 32768]
input_3fp32 [32768, 32768]
definition comparatornot_asserted
Measurements
latency · max9.05 ms · n=100
latency · mean9.00 ms · n=100
latency · min8.99 ms · n=100
latency · std7.92 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
Show manifestHide manifest
{
"run": {
"kind": "BenchmarkRun",
"spec": {
"status": "passed",
"timing": {
"samples": 100,
"latencyNs": {
"mean": 9000000,
"maximum": 9050000,
"minimum": 8990000,
"confidence95": [
8998448,
9001552
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 7920,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 9.05,
"min_ms": 8.99,
"std_ms": 0.00792,
"mean_ms": 9
},
"benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch.json",
"externalId": "H100_PCIe_LambdaLabs/torch/level1/96_HuberLoss.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:b29e82548e8c78a362b37ca97fee35133a99efc99bbb7bb042bcb56d6fbba1e0",
"environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
"implementationDigest": "sha256:85a252d7cc7b1d5cdfc464ba3c5f1313368624d0d2b5239b7060cc16cbaab2a8"
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs-torch-l1-96-huberloss",
"title": "HuberLoss · PyTorch eager · Lambda Labs"
},
"apiVersion": "kernelindex.dev/v1alpha1"
},
"protocol": {
"kind": "BenchmarkProtocol",
"spec": {
"harness": {
"name": "KernelBench timing scripts",
"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"
},
"environment": {
"kind": "ExecutionEnvironment",
"spec": {
"hardware": {
"vendor": "nvidia",
"product": "NVIDIA H100",
"formFactor": "PCIe",
"architecture": "sm_90"
},
"software": {}
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs",
"title": "KernelBench host · H100 PCIe (Lambda Labs)"
},
"apiVersion": "kernelindex.dev/v1alpha1"
}
}Cite this record (permalink, digest, access date)
Report an issue with this run
Published 2026-08-26 · KernelBench baseline timings · MITAll results for HuberLoss →JSON