R2ABench (MetaGPT) - GED Accuracy: leaderboard
Metric: Normalized graph-edit-distance accuracy (0-100) between the generated and reference architecture graphs (L1), over the 68 R2ABench projects (17 educational and 51 GitHub repositories), generating a PlantUML architecture view from the structured requirements specification with MetaGPT adapted as an analyst, architect, reviewer and refiner agent pipeline under default settings and greedy decoding; scored only over the outputs that render and parse (the L0 gate), failed outputs excluded; higher is better. Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 4 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | MetaGPT + DeepSeek V3.2 | 50.27 |
| 2 | MetaGPT + Qwen3-Coder 480B-A35B | 49.12 |
| 3 | MetaGPT + Claude Sonnet 4.6 | 48.26 |
| 4 | MetaGPT + GPT-5 | 46.38 |
Interactive version: theaggregate.ai/benchmark?slug=r2abench-metagpt-ged-accuracy · How It Works · Data refreshed daily, snapshot 2026-10-07.