DRQ Benchmark
Multi-Provider LLM Core War Arena
Challenge
Evaluating LLM code generation requires controlled benchmarks with measurable outcomes. The original DRQ (Digital Red Queen) research showed convergent evolution in LLM-generated programs, but single-provider evaluation limits insights. Building a fair multi-model battle arena requires consistent prompting, parallel generation, and deterministic battle simulation.
Solution
DRQ Benchmark extends the original research with multi-provider LLM support across leading models. Warriors generated by different models compete in Core War, with parallel generation significantly reducing benchmark time.
Results
- Multi-provider LLM support across leading models
- Real-time web monitoring interface
- Pygame battle visualization
- Significantly faster with parallel warrior generation
- Player vs Player mode (any model combination)
- Battle history with localStorage persistence
System Architecture
Multi-provider LLM battle arena for adversarial program evolution research
Multi-provider LLM battle arena for adversarial program evolution research
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