BenSyc: leaderboard
BenSyc (2026) asks models to classify replies in emotionally charged Bengali and Banglish Reddit conversations on a five-level alignment scale from invalidation through neutral, support and validation to escalation. Scored by macro-F1 in percent against human labels; higher is better.
Metric: Five-class conversational alignment classification macro-F1 (%) (invalidation, neutral, support, validation, escalation) on human-annotated Bengali and Banglish Reddit replies from Bangladesh and West Bengal communities, deterministic decoding (temperature 0), open models via Ollama; the paper ranks the leaderboard by this score; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 15 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemma 4 31B | 61.7 | #394 |
| 2 | GPT-5.4 Mini | 57.2 | #389 |
| 3 | Qwen 2.5 32B | 55.4 | #1332 |
| 4 | Llama 3.3 70B | 54.3 | #1498 |
| 5 | Qwen 2.5 14B | 44.2 | #1785 |
| 6 | Llama 3.1 8B | 41.2 | #4861 |
| 7 | Gemma 2 9B | 40.3 | #2802 |
| 8 | Qwen 2.5 7B | 38.2 | #2703 |
| 9 | Gemma 2 27B | 38.2 | #2108 |
| 10 | Mixtral 8x7B Instruct | 33.2 | #4444 |
| 11 | Mistral 7B Instruct | 30.5 | #7468 |
| 12 | Llama 3.2 3B | 21.3 | #7830 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=bensyc · How It Works · Data refreshed daily, snapshot 2026-11-13.