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GroupNorm

42 eligible runs
groupnorm

Group normalization of a batch×channels×hidden tensor with affine channel weight and bias; groups = channels / channels_per_group.

Fastest reported · usable today
17.5µsmedian · 1.75× faster than baseline
LigerLiger-Kernel · BSD-2-Clause · triton

Reported evidence · last observed 2026-02-28. Reported by source; not independently reproduced.

pip install "liger-kernel==0.7.0"

Fastest by languagetriton · Liger · 17.5 µs · #1python · Transformers · 30.7 µs · 1.75×

Current records

Source-native comparison · GPU NVIDIA B200 · Workload batch = 128 · hidden = 512 · channels = 32 · channels_per_group = 4 · fp32 · Protocol Liger-Kernel benchmark scripts · median · 2 results · last observed 2026-02-28Record history →
Estimated floor 1.05 µs · record 16.72× above itestimate, not evidence ›
DRAM 1.05 µs · bandwidth-bound on B200
every declared tensor crosses HBM exactly once (8,000 GB/s, B200 datasheet)
no arithmetic formula for this family: bandwidth floor only
headroom-v1: a lower bound from declared tensors and datasheet peaks. A kernel can sit well above it for good reasons.
#
Implementation
Latency
vs #1
Trust
Observed
1
LigerLiger-Kernel
17.5µs
1.00×
Reported · BSD-2-Clause · source
2026-02-28stale

1.75× faster than the baseline. Measured exactly what you asked. Reported by source; not independently reproduced.

source mirroredBSD-2-ClauseinstallableView source →Run detail →
2
TransformersbaselineHugging Face Transformers
30.7µs
1.75×
Reported · Apache-2.0 · source
2026-02-28stale

Measured exactly what you asked. The source's designated baseline implementation. Reported by source; not independently reproduced.

source mirroredApache-2.0no install recipeView source →Run detail →

Scaling by channels

100.0 µs1.00 ms326412825651210242048channels →17.5 µs18.8 µs26.6 µs38.9 µs63.5 µs114.8 µs219.1 µsLiger30.7 µs43.0 µs71.7 µs135.2 µs258.1 µs498.6 µs981.9 µsTransformers
LigerTransformersbest per workload · NVIDIA B200 · Liger-Kernel benchmark scripts held constant · log scale

Implementations

Implementation
Runtime
Best latency
Evidence
Availability
TransformersHugging Face Transformers
python
30.7µs
1.75×
Reported
Apache-2.0 · source
LigerLiger-Kernel
triton
17.5µs
1.00×
Reported
BSD-2-Clause · source

Semantics

Inputs and outputs
xfloat [batch, channels, hidden]
weightfloat [channels]
biasfloat [channels]
yfloat [batch, channels, hidden]
Axes and behavior
batchvariable
groupsgroups = channels // channels_per_group
hiddenvariable
channelsvariable
determinismunspecified
constraintsNo mutation or aliasing
Identity
sha256a5be9b2fb0c7…
Sources: Liger-Kernel benchmarks (2026-02-28) · BSD-2-Clauselast observed 2026-02-28How records are decidedJSON