discover_sorting

hardcomparatorsPython
results

Measured by number of comparators used — lower is better.

80 comparators60 comparators
sota
Claude-Opus-4.6
reward 1.000

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-only

Rules

  • 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
Claude-Opus-4.6
1.000
Gemini-3.1-Pro
0.950
Kimi-K2.6
0.900
MiMo-V2.5-Pro
0.900
GLM-5
0.850
GPT-5.4
0.850
Grok-4-20
0.850
DeepSeek-V4-Pro
0.570
Qwen-3.6-Plus
0.570
Hunyuan-3-Preview
0.250
MiniMax-M2.7
0.000