Few-Shot Chain-of-Thought Consistently Outperforms

In benchmarking six top prompting techniques against ChatGPT using the MMLU dataset, Few-Shot Chain-of-Thought (CoT) consistently delivered superior results.

CoT prompting provides examples that include explicit reasoning steps, not just input-output pairs. The model sees not only what to produce but how to think through the problem. This combination of exemplars plus demonstrated reasoning creates a powerful scaffold for complex tasks.

The technique works especially well on reasoning and multi-step problem-solving tasks where showing the intermediate steps helps the model construct valid reasoning paths.

The pattern: don’t just show the answer, show the work.

Related: 05-molecule—chain-of-thought-prompting, 05-atom—in-context-learning-definition