GPT-3.5 models can understand and generate natural language or code. Our most capable and cost effective model in the GPT-3.5 family is gpt-3.5-turbo which has been optimized for chat but works well for traditional completions tasks as well. LATEST MODEL | DESCRIPTION | MAX TOKENS | TRAINING DATA |
---|
gpt-3.5-turbo | Most capable GPT-3.5 model and optimized for chat at 1/10th the cost of text-davinci-003 . Will be updated with our latest model iteration. | 4,096 tokens | Up to Sep 2021 | gpt-3.5-turbo-0301 | Snapshot of gpt-3.5-turbo from March 1st 2023. Unlike gpt-3.5-turbo , this model will not receive updates, and will only be supported for a three month period ending on June 1st 2023. | 4,096 tokens | Up to Sep 2021 | text-davinci-003 | Can do any language task with better quality, longer output, and consistent instruction-following than the curie, babbage, or ada models. Also supports inserting completions within text. | 4,097 tokens | Up to Jun 2021 | text-davinci-002 | Similar capabilities to text-davinci-003 but trained with supervised fine-tuning instead of reinforcement learning | 4,097 tokens | Up to Jun 2021 | code-davinci-002 | Optimized for code-completion tasks Now deprecated | 8,001 tokens | Up to Jun 2021 |
Recommendation to use gpt-3.5-turbo over the other GPT-3.5 models because of its lower cost. Experimenting with gpt-3.5-turbo is a great way to find out what the API is capable of doing. After you have an idea of what you want to accomplish, you can stay with gpt-3.5-turbo or another model and try to optimize around its capabilities. Note: OpenAI models are non-deterministic, meaning that identical inputs can yield different outputs. Setting temperature to 0 will make the outputs mostly deterministic, but a small amount of variability may remain. |