7 Counterintuitive LLM Facts Most Developers Get Wrong

Think longer prompts always perform better? Bigger context windows mean smarter outputs? More parameters equal higher accuracy? These common assumptions are actually traps. We break down the most misunderstood counterintuitive facts in the LLM industry—like the 「lost-in-the-middle」 effect in Claude Opus 4.8 long-doc tasks, how DeepSeek R1 chain-of-thought length paradoxically increases self-contradiction rate, and why Gemini 3 multimodal token billing costs 3x more than developers expect. Every point is grounded in real benchmarks, not speculation. Master these, and you'll save months of costly trial and error. By the way, XycAi connects you to 200+ models including GPT-5.5, Claude, Gemini, and DeepSeek through a single API.