PyTorch
Multi-token attention · k = 3 · seq = 1024 · batch = 2 · heads_in = 4 · heads_out = 4 · bf16 · run 01a0202b-2190…
●passedReported evidence
Not re-observed recently.
Primary measurement
719.9µsmedian
Rank 2 in its comparison group · source-native comparison · observed 2025-04-28
ms 20 0.7167999744415283 · ms 50 0.719871997833252 · ms 80 0.7260159850120544
Identity
implementationPyTorch
projectPyTorch
revisionunknown
workloadk = 3 · seq = 1024 · batch = 2 · heads_in = 4 · heads_out = 4 · bf16
comparison keysha256:e5fc245d0301c8ab…
sourceLiger-Kernel benchmarks
external idmulti_token_attention/forward/torch/nvidia-geforce-rtx-3090/batch2-heads_in4-heads_out4-k3-seq1024-bf16/2025-04-28-04-46-11
sha256:3b5c84a59072897ff201935…
Correctness
Marked passed by the source; the correctness policy was not published.
Workload
k3
seq1024
batch2
heads_in4
heads_out4
biasbf16 [4]
scoresbf16 [2, 4, 1024, 1024]
weightbf16 [4, 4, 3, 3]
definition comparatornot_asserted
Measurements
latency · median719.9 µs
latency · p20716.8 µs
latency · p80726.0 µs
Protocol
harnessLiger-Kernel benchmark scripts
timercuda_events
primaryStatisticmedian
comparabilityFamilyliger_kernel_bench
Environment
gpuNVIDIA GeForce RTX 3090 (sm_86)
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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}
}Cite this record (permalink, digest, access date)
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Published 2026-08-20 · Liger-Kernel benchmarks · BSD-2-ClauseAll results for Multi-token attention →JSON