BenSyc - Binary Detection: leaderboard
Metric: Binary sycophancy detection macro-F1 (%) (sycophantic versus non-sycophantic reply) on human-annotated Bengali and Banglish Reddit replies from Bangladesh and West Bengal communities, deterministic decoding (temperature 0), open models via Ollama; higher is better. Source: arxiv.org. Saturation forecast: Around 2030. 15 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Llama 3.3 70B | 61.8 |
| 2 | Qwen 2.5 32B | 58.4 |
| 3 | GPT-5.4 Mini | 57.5 |
| 4 | Qwen 2.5 7B | 56.9 |
| 5 | Qwen 2.5 14B | 56.9 |
| 6 | Llama 3.1 8B | 55.5 |
| 7 | Gemma 2 27B | 55 |
| 8 | Llama 3.2 3B | 53.5 |
| 9 | Gemma 4 31B | 51.2 |
| 10 | Gemma 2 9B | 50.6 |
| 11 | Mixtral 8x7B | 49.4 |
| 12 | Mistral 7B Instruct | 43.7 |
Interactive version: theaggregate.ai/benchmark?slug=bensyc-binary-detection · How It Works · Data refreshed daily, snapshot 2026-09-29.