Pseudo-Deliberation in Language Models: leaderboard
Large language models (LLMs) are often evaluated based on their stated values, yet these do not reliably translate into their actions, a discrepancy termed "value-action gap." In this work, we argue that this gap persists even under explicit reasoning, revealing a deeper failure mode we call "Pseudo-Deliberation": the appearance of principled reasoning without corresponding behavioral alignmen
Metric: Fast Thinking Macro F1 (self-reported). Source: benchmarklist.com. Saturation forecast: Around April 2027. 4 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 3 Flash | 47.72 | #99 |
| 2 | Llama 3 8B Instruct | 47.7 | #1129 |
| 3 | GPT-4o | 45.28 | #343 |
| 4 | Qwen 3 8B | 44.2 | #674 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=pseudo-deliberation-in-language-models · How It Works · Data refreshed daily, snapshot 2026-10-20.