discover_sorting
hardcomparatorsPython
results
Measured by number of comparators used — lower is better.
80 comparators60 comparators
sota
Usage
Run the reference answer to verify your environment is set up correctly
$ harbor run -p tasks/discover_sorting
Test model
$ harbor run -p tasks/discover_sorting \ -a claude-code -m claude-opus-4-6
Description
Generate a correct 16-input sorting network using as few comparators as possible. A sorting network is a fixed sequence of compare-exchange operations, and correctness is verified exhaustively on all 65,536 binary inputs using the zero-one principle.
Files
path
permission
/app/solve.py✎ Edit/app/main.pyRead-onlyRules
- 01Edit /app/solve.py only. Python standard library only.
- 02generate_network() must return a list of 2-tuples with 0 <= i, j < 16 and i != j.
- 03Incorrect networks score 0.
Tags
pythonsorting-networksearchcombinatorial-optimization0-1-principle
Model Results
Click a row to view its trajectory in Live Lab
model
reward
score
1.000
0.950
Kimi-K2.6
0.900
MiMo-V2.5-Pro
0.900
0.850
0.850
Grok-4-20
0.850
DeepSeek-V4-Pro
0.570
Qwen-3.6-Plus
0.570
Hunyuan-3-Preview
0.250
0.000