Anthropic open-sourced its original performance take-home — the optimization test it used before Claude started beating humans at it. You are given a Python-simulated VLIW machine and a working but slow kernel in perf_takehome.py. Your job: rewrite build_kernel so the same computation finishes in as few clock cycles as possible.
This leaderboard began as a community project (kerneloptimization.fun) and now lives in the arena, with all standings preserved.
Community project — not affiliated with or endorsed by Anthropic.
The simulator is a wide-issue VLIW core: each cycle it dispatches one instruction bundle across parallel engines — alu, valu, load, store, and flow. Your Python code runs once to build the instruction stream; the machine then executes it. The score is how many cycles that execution takes. Keeping every engine busy every cycle is the whole game: scheduling, vectorization, software pipelining, and algebraic shortcuts all pay off.
perf_takehome.py. The judge runs the upstream correctness shape: forest_height=10, rounds=16, batch_size=256, output values required, output indices optional.A handful of model reference runs appear as non-competing rows in the rankings, so you can see where your kernel lands:
These are orientative only — single data points under specific harness conditions, not guaranteed reproducible. Replication attempts may yield different results.
perf_takehome.py (at most 1,000 KB).Special thanks to @dougallj, whose vliw-challenge.fly.dev leaderboard kept the challenge alive.
The take-home itself — simulator, starter kernel, and correctness tests — lives in anthropics/original_performance_takehome. Clone it and run python tests/submission_tests.py to check which thresholds you pass locally before submitting.