
Unlocking Creativity with Azure OpenAI
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In the world of Large Language Models (LLMs), a context window defines the amount of text a model can process at once, impacting how it generates and comprehends language. This window is measured by the number of tokens (either whole words or fragments), directly affecting how much information the model uses to predict the next token. In simple terms, it dictates how much context the model takes into account when forming predictions or crafting responses.
For example, the GPT-3.5-Turbo (0125) model context has 16,385 input tokens and 4,096 output tokens, while the GPT-4o and GPT-4o mini models have a much larger number at 128,000 input tokens and 16,384 output tokens. For information about the context window of AOAI models, visit https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models?#gpt-4-and-gpt-4-turbo-models.
The trend in LLMs is moving toward bigger context windows, which enable more detailed and coherent outputs. However, this...