User Frustration Mounts Over GPT-5.2’s Perceived Lack of Deep Thinking Capabilities

User Frustration Mounts Over GPT-5.2’s Perceived Lack of Deep Thinking Capabilities

A growing number of users are expressing frustration with OpenAI’s GPT-5.2 model, citing its apparent reluctance to engage in prolonged or complex reasoning tasks. One Reddit user, identified as /u/Swimming-Square-3173, posted a widely shared complaint: "It does not matter if I tell it to think harder or longer. It does not matter if I use iOS or WEB. Will this be fixed?" The user concluded by reverting to GPT-5.1, signaling a loss of confidence in the newer iteration.

While OpenAI has not publicly acknowledged the issue, the pattern of complaints suggests a broader disconnect between user expectations and the model’s operational design. Many users anticipated that incremental updates would enhance the model’s capacity for deep, step-by-step reasoning — a feature previously associated with earlier versions. Instead, some report that GPT-5.2 appears to prioritize speed and brevity over depth, often defaulting to surface-level responses even when prompted to "think harder" or "explain in detail."

Language experts note that the word "really" — frequently used in these user complaints — carries nuanced emphasis in English. According to Cambridge Dictionary, "really" is commonly employed as an adverb to intensify adjectives or adverbs, as in "It’s really hard to find a decent job" — mirroring users’ frustration: "I am really annoyed." Merriam-Webster further defines "really" as "in reality" or "actually," underscoring the user’s sense that the model’s behavior contradicts its advertised capabilities. This linguistic emphasis reveals a deeper cognitive dissonance: users believe they are interacting with a system designed for analytical depth, yet experience something that feels superficial.

Dictionary.com’s entries on "really" highlight its role in everyday digital discourse, particularly in contexts involving personal experience and subjective evaluation — precisely the terrain where AI interactions are most scrutinized. When users say, "It doesn’t matter what I do," they are not merely complaining about a glitch; they are signaling a breakdown in trust. The perceived inability of GPT-5.2 to "think" as expected may reflect either an intentional shift toward efficiency (to reduce latency and computational cost) or an unaddressed regression in reasoning fidelity.

Analysts suggest that OpenAI may have optimized GPT-5.2 for high-volume, low-latency applications — such as customer service bots or mobile assistants — at the expense of complex, multi-step problem solving. This trade-off is common in AI development, where scaling for accessibility often compromises depth. However, users in technical, academic, and creative fields rely on AI for precisely those deeper cognitive tasks, making this shift particularly disruptive.

As of now, OpenAI has released no official statement regarding changes to GPT-5.2’s reasoning architecture. Community forums are flooded with workarounds: users are appending phrases like "Show your work," "Break it down," or "Assume you’re an expert" in hopes of triggering deeper responses. Some have reverted to GPT-5.1, while others are exploring alternative models from Anthropic or Google’s Gemini.

The episode highlights a critical tension in AI development: the gap between what users perceive as "thinking" and what machine learning models are engineered to simulate. While GPT-5.2 may be statistically more accurate and contextually coherent, its failure to meet the emotional and cognitive expectations of its users suggests a need for greater transparency in model capabilities — and perhaps, a redefinition of what "thinking" means in the context of artificial intelligence.

For now, the message from the user base is clear: if AI cannot be trusted to think deeply, then its value diminishes — regardless of how "really" fast it responds.