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GQA paged prefill causal h24 kv8 d128 ps64

19 eligible runs
gqa-paged-attention

Batched Grouped Query Attention prefill with a paged KV cache (page_size=64). Causal mask applied. From Llama 3.2 3B. 24 q-heads, 8 kv-heads, head_dim=128.

Source baseline · unbeaten
39.0µsmean
flashinfer / wrapper92685dFlashInfer-Bench baselines · Apache-2.0 · python

Reported evidence · last observed 2026-04-12. The source's designated baseline implementation. Reported by source; not independently reproduced.

Current records

Not measured on H100, B200 for this workload. Challenges →

Source-native comparison · GPU NVIDIA GB200 · Workload total_q = 1 · num_pages = 17 · len_indptr = 2 · num_kv_indices = 1 · bf16 · CUDA 13.0 · Framework pytorch 2.9.1+cu130 · Protocol flashinfer-bench · mean · 1 results · last observed 2026-04-12Record history →
Estimated floor 558 ns · record 69.88× above itestimate, not evidence ›
DRAM 558 ns · bandwidth-bound on GB200
every declared tensor crosses HBM exactly once (8,000 GB/s, GB200 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.
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Implementation
Latency
vs #1
Trust
Observed
1
flashinfer / wrapper92685dbaselineFlashInfer-Bench baselines
39.0µs
1.00×
Reported · Apache-2.0 · source
2026-04-12

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 →

Implementations

Implementation
Runtime
Best latency
Evidence
Availability
flashinfer / wrapper92685dFlashInfer-Bench baselines
python
39.0µs
1.00×
Reproduction-ready
Apache-2.0 · source

Semantics

Inputs and outputs
qbf16 [total_q, num_qo_heads, head_dim]
k_cachebf16 [num_pages, page_size, num_kv_heads, head_dim]
v_cachebf16 [num_pages, page_size, num_kv_heads, head_dim]
qo_indptrint32 [len_indptr]
kv_indptrint32 [len_indptr]
kv_indicesint32 [num_kv_indices]
kv_last_page_lenint32 [len_indptr]
sm_scalefp32 scalar
outputbf16 [total_q, num_qo_heads, head_dim]
lsefp32 [total_q, num_qo_heads]
Axes and behavior
total_qvariable
head_dimconstant = 128
num_pagesvariable
page_sizeconstant = 64
len_indptrvariable
num_kv_headsconstant = 8
num_qo_headsconstant = 24
num_kv_indicesvariable
determinismunspecified
constraintsNo mutation or aliasing
Identity
aliasgqa_paged_prefill_causal_h24_kv8_d128_ps64modelllama-3-2-3bsha25656952fa7d908…
Sources: FlashInfer-Bench (2026-04-12) · Apache-2.0last observed 2026-04-12How records are decidedJSON