PyTorch eager
Tanh · dim = 393216 · batch_size = 4096 · fp32 · run 01a03f0e-f831…
●passedReported evidence
Not re-observed recently.
Primary measurement
6.95ms±0.00 · mean of 100
Rank 1 in its comparison group · source-native comparison · observed 2026-03-05
max ms 6.98 · min ms 6.94 · std ms 0.00607 · mean ms 6.95
Identity
implementationPyTorch eager
projectPyTorch
revisionunknown
workloaddim = 393216 · batch_size = 4096 · fp32
comparison keysha256:afadee16bfcc55e3…
sourceKernelBench baseline timings
external idH100_PCIe_LambdaLabs/torch/level1/22_Tanh.py
sha256:1b55399cea0a93763bab1fd…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
dim393216
batch_size4096
xfp32 [4096, 393216]
definition comparatornot_asserted
Measurements
latency · max6.98 ms · n=100
latency · mean6.95 ms · n=100
latency · min6.94 ms · n=100
latency · std6.07 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": 6950000,
"maximum": 6980000,
"minimum": 6940000,
"confidence95": [
6948810,
6951190
]
},
"primaryStatistic": "mean"
},
"observedAt": "2026-03-05T08:38:15.000Z",
"measurements": [
{
"unit": "ns",
"value": 6070,
"metric": "latency",
"statistic": "std"
}
],
"sourceNative": {
"source": "kernelbench",
"metrics": {
"max_ms": 6.98,
"min_ms": 6.94,
"std_ms": 0.00607,
"mean_ms": 6.95
},
"benchmark": "H100_PCIe_LambdaLabs/baseline_time_torch.json",
"externalId": "H100_PCIe_LambdaLabs/torch/level1/22_Tanh.py"
},
"protocolDigest": "sha256:547725b033a9911eae0c5ac362344a85aed824894ed4ab476af945b9bb491ea6",
"workloadDigest": "sha256:6973fa702edcc801f36b06b9189b1b454d1b0e96b31c32da5cd4f0a7b8b5a8f0",
"environmentDigest": "sha256:89f9b28b06758f22a1df331fea58bfde2c9cc0f3627d1829509743ea538f0011",
"implementationDigest": "sha256:2874220e1cae6df54972fa588d29bcb5c40cd02052c7d46656b45b211b5caaaa"
},
"metadata": {
"name": "kernelbench-h100-pcie-lambdalabs-torch-l1-22-tanh",
"title": "Tanh · 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"
},
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"environment": {
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},
"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)
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Published 2026-08-26 · KernelBench baseline timings · MITAll results for Tanh →JSON