KernelBench operators
Faster GPU kernels for PyTorch operators, exactly as correct as the reference (placeholder)
KernelBench operators
Placeholder. This benchmark is here so the benchmark panel can be tried out. Its baseline is from the blueprint or the literature as of 2026-10-19 and must be checked again; every route and score after it is made up.
Task
Write GPU kernels that compute what twelve PyTorch operators and modules from Stanford’s KernelBench compute, faster. A kernel counts only if it matches the PyTorch reference on random inputs. The score is the geometric mean speed-up over PyTorch eager on the pinned runner, so the baseline is exactly 1. Triton, CUDA and anything else that compiles on the runner is fine.
How to take part
Start a route from main (the baseline) or from any route on the leaderboard, keep your files in the route's folder, and push: the verifier scores every commit. Say what your route changes with tags, and keep the misses: a route that scores worse is a result too.