o1: OpenAI's NEW Prompting Advice

THIS IS TAKEN FROM THEIR DEVELOPER PAGES.

These models perform best with straightforward prompts. Some prompt engineering techniques, like few-shot prompting or instructing the model to "think step by step," may not enhance performance and can sometimes hinder it. Here are some best practices:

Keep prompts simple and direct: The models excel at understanding and responding to brief, clear instructions without the need for extensive guidance.
Avoid chain-of-thought prompts: Since these models perform reasoning internally, prompting them to "think step by step" or "explain your reasoning" is unnecessary.
Use delimiters for clarity: Use delimiters like triple quotation marks, XML tags, or section titles to clearly indicate distinct parts of the input, helping the model interpret different sections appropriately.
Limit additional context in retrieval-augmented generation (RAG): When providing additional context or documents, include only the most relevant information to prevent the model from overcomplicating its response.

Reasoning Models

OpenAI o1 series models are new large language models trained with reinforcement learning to perform complex reasoning. o1 models think before they answer, and can produce a long internal chain of thought before responding to the user. o1 models excel in scientific reasoning, ranking in the 89th percentile on competitive programming questions (Codeforces), placing among the top 500 students in the US in a qualifier for the USA Math Olympiad (AIME), and exceeding human PhD-level accuracy on a benchmark of physics, biology, and chemistry problems (GPQA).

There are two reasoning models available in the API:

o1-preview: an early preview of our o1 model, designed to reason about hard problems using broad general knowledge about the world.
o1-mini: a faster and cheaper version of o1, particularly adept at coding, math, and science tasks where extensive general knowledge isn't required.

o1 models offer significant advancements in reasoning, but they are not intended to replace GPT-4o in all use-cases.

For applications that need image inputs, function calling, or consistently fast response times, the GPT-4o and GPT-4o mini models will continue to be the right choice. However, if you're aiming to develop applications that demand deep reasoning and can accommodate longer response times, the o1 models could be an excellent choice. We're excited to see what you'll create with them!

https://platform.openai.com/docs/guides/reasoning

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