Seeking Small ~10B LLMs That Resist Sycophancy and Act as Critical Collaborators

A user on the r/LocalLLaMA subreddit asked the community for recommendations of small open-weights language models (~10B parameters) capable of critically evaluating ideas and pushing back on flawed premises. The user noted that while recent ~10B models score high on standard benchmarks, they often suffer from sycophancy and are overly optimized for one-shot task completion. This discussion highlights a key gap between standard benchmark metrics and real-world utility for local AI users. Identifying small models that can constructively challenge user ideas allows developers with constrained GPU hardware to run effective brainstorming partners locally. The request specifically targets models around the 10-billion-parameter threshold to fit consumer GPU VRAM limits. The user expressed a preference for multi-turn collaboration where the model points out logical errors, rather than sycophantically accepting every prompt assumption.