OpenAI’s GPT-5 has been introduced as the company’s most advanced AI model yet, with major improvements in accuracy and reasoning. One of the key changes highlighted by the company is a significant reduction in hallucination, the term used when AI produces information that is false or misleading. This improvement is intended to make the model more reliable for complex tasks, whether it is answering questions, assisting with research, or generating creative content.
The model’s new “thinking” mode, combined with better training data and refined safety mechanisms, is designed to provide responses that are both more accurate and more transparent about uncertainty. GPT-5 is also more likely to admit when it does not know something instead of providing a confident but incorrect answer. These updates represent OpenAI’s ongoing effort to address one of the biggest criticisms of previous AI models – that they often produce convincing but factually incorrect information.
According to the system card for GPT-5, the reduction in hallucination is measurable and varies across modes:
- GPT-5-thinking with browsing: 4.5% hallucination rate
- GPT-5-main: 9.6% hallucination rate
- o3: 12.7% hallucination rate
- GPT-4o: 12.9% hallucination rate
Despite these advancements, GPT-5 is not flawless. Tests have shown that while hallucination rates have dropped compared to GPT-4o, the model can still make basic errors. Examples include mistakes in spelling, misidentifying geographical locations, and creating details that do not exist. These errors highlight that, while accuracy has improved, the model’s ability to guarantee factual correctness is still limited. This means that users should continue to verify AI-generated content before relying on it for important decisions.
The launch of GPT-5 also sparked debate about how AI is presented to the public. Visuals and promotional materials used during the announcement were later criticized for misrepresenting certain statistics, prompting clarifications. This raised questions about transparency not only in the AI’s responses but also in how its capabilities are communicated.
The improvements in GPT-5 mark a step forward for AI reliability, but they also serve as a reminder that no AI model is perfect. Even with reduced hallucination rates, the technology still depends on patterns in data rather than a true understanding of facts. For applications in education, journalism, healthcare, and other high-stakes fields, human oversight remains essential.
Overall, GPT-5 moves closer to the goal of a more trustworthy AI assistant, but caution is still necessary. The model’s strengths in reasoning, creativity, and conversational ability are clear, yet so are its weaknesses when dealing with factual precision. As AI technology continues to evolve, the balance between fluency and accuracy will remain at the heart of the conversation.
