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Reasoning models, like Gemini 2.0 Flash Thinking Experimental, approach problem-solving differently than traditional large language models (LLMs). Given a prompt, these models pause to consider related questions and explain their reasoning before summarizing what they believe to be the most accurate response. Jeff Dean, Chief Scientist for Google DeepMind, noted that this model was “trained to use thoughts to strengthen its reasoning,” and said the company sees promising results when increasing inference time computation—essentially giving the model more time and resources to process queries.
The trade-off? Time. Unlike conventional LLMs, reasoning models often take significantly longer to respond—sometimes seconds or even minutes. ...
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