Why can generative AI tools be inconsistent in their responses to the same prompt?

You can ask the same model the exact same question and get a slightly differently worded response. The AI may interpret the prompt in different ways, especially if the prompt is open ended or vague. Most tools also have settings to make them spontaneous and human-like. This degree of randomness is sometimes called ‘temperature control’ of output.

AI tools may apply a deterministic model to its learning and so will predict a more consistent response to the same prompt. Some may take the recent conversation history into account to provide a context for the response. Other tools will apply a stochastic model which adds randomness and uncertainty to the learning, a range of possible outcomes may be predicted, leading to a different response to the same prompt. Creating specific prompts with custom instruction and fine-tuning will help to reduce variation.

Ultimately LLMs are mathematically generating likely responses on a token by token basis and always generating the same response would be a noteworthy situation.

If it’s important for a generative AI tool to be consistent in its output for the same prompt, test the same prompt several times with different tools, and choose a tool that provides the consistency you’re looking for.