kernelbench.com

Model · Alibaba

qwen3.8-max-preview

1 bench deck · 0/6 problems correct on canonical boards · 1 audited cells.

methodology + notes

How to read. Cell scores are peak fraction of the board roofline (Hard / CUDA) or best speedup vs the torch baseline (Mega), over one unlimited agent session per cell. Audit chips come from the human/subagent reward-hack review of every published cell; scores from flagged sessions render dimmed — they don't count toward the charts.

Board summary bars are each score relative to the best published model on that board (1.00 = board leader); the printed number is the bench-native score.

Methodology. Rank per bench: valid passes (audited-clean correct cells / problems) desc, then mean normalized performance over the FULL problem deck (cell score / board best per problem; fail/invalid/missing cells count as 0) desc. Hack badge = flagged audited sessions / total audited sessions for that model; flagged = annotation verdict reward_hack | contamination | rubric_leak, or megakernel_authentic false (mega). Verdicts come from per-run audit YAMLs, not static lint. Hack rate is displayed, never a sort key. Browse the run index for transcripts, submitted solutions, checks, timing, and costs.

Board summarybars = share of each board's best model · numbers = bench-native score
Hard
0/6
Hard
0/6 pass1 audited

RTX PRO 6000· canonical board

FP8 GEMMpass
37.3%clean
KDA CUTLASSno run
Paged Attentionno run
TopK Bitonicno run
Sonic MoEno run
W4A16 GEMMno run

all audited selected attempts

Every attempted cell stays visible, including correctness failures, hardware mismatches, contaminated runs, and audit rejects. Only publishable results contribute to the board above.

unknown GPU · FP8 GEMMclean
37.29%audit evidence

Genuine fp8 x fp8 Triton tl.dot GEMM with fp32 accumulate, per-output-channel scale epilogue, bf16 store. Autotuned config space (BM/BN/BK up to 128x256x128, num_stages 3-4) with an M-bucketed early_config_prune splitting decode-skinny from fat tiles, and grouped L2 swizzle. Off-alignment K (4127) is zero-padded to a multiple of 128 so the K loop is even and unmasked (TMA/cp.async-friendly); x is copied into its pad buffer EVERY call, only the padded weight is cached, invalidated via weight._version. Empirically verified to recompute on in-place input and weight mutation. Transcript contains only its own run id; KBH_NUMERIC_STRESS only ever set to =1 (extra strictness). 0.3729 geomean in-run, honest.

audited run