A company wants an Amazon Bedrock LLM to give more consistent outputs for the same input prompt. Which inference parameter change will make the model responses more deterministic?

Decreasing the temperature value makes the model's responses more deterministic. Temperature controls the randomness of the output; a lower temperature (closer to 0) makes the model more conservative and predictable, choosing the most probable next token. This results in more consistent outputs for the same input prompt. Increasing the temperature value would make the outputs more random and creative. Decreasing or increasing the length of output tokens or the maximum generation length primarily affects the length of the response, not its determinism or consistency.