QuantumComputing
Task 33 / 47
task_03_cross_target_qaoa
Cross-target robust optimization for QAOA-style variational parameters across instances or perturbations, improving mean or worst-case objective values. It captures robustness needs for VQAs when problem instances or noise conditions shift—an engineering angle on quantum heuristic performance.
Model leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | DeepSeek V3.2 | 100.0 |
| 2 | GLM-5 | 97.3 |
| 3 | Gemini 3.1 Pro Preview | 21.0 |
| 4 | SEED 2.0 Pro | 21.0 |
| 5 | Grok 4.20 | 8.2 |
| 6 | Claude Opus 4.6 | 6.1 |
| 7 | Qwen3 Coder Next | 1.4 |
| 8 | GPT-5.4 | 0.0 |
Framework leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-OSS + OpenEvolve | 100.0 |
| 2 | GPT-OSS + ShinkaiEvolve | 99.8 |
| 3 | GPT-OSS + ABMCTS | 99.7 |
| 4 | Claude Opus 4.6 + ShinkaiEvolve | 18.4 |
| 5 | Claude Opus 4.6 + ABMCTS | 0.0 |
| 6 | Claude Opus 4.6 + OpenEvolve | 0.0 |
Score is the normalized score for this task (0–100, higher is better).