I Benchmarked 6 Prompting Strategies on Two Models. The Winner Changes Depending on Which Model You Ask.
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Over two weeks, I built a small evaluation harness to test whether popular prompting techniques — few-shot examples, Chain-of-Thought, self-consistency voting, Tree-of-Thought — actually improve accuracy, and at what cost. I ran everything on 20 fixed GSM8K math word problems, first against a free local model (Mistral-7B via Ollama), then again against GPT-4o-mini via the OpenAI API, using identical questions and prompts. Full code and raw results: github.com/Mohsin2686/prompt-bench The…
1Key Takeaways
- Over two weeks, I built a small evaluation harness to test whether popular prompting techniques — few-shot examples, Chain-of-Thought, self-consistency voting, Tree-of-Thought — actually improve accuracy, and at what cost.
- I ran everything on 20 fixed GSM8K math word problems, first against a free local model (Mistral-7B via Ollama), then again against GPT-4o-mini via the OpenAI API, using identical questions and prompts.
- Full code and raw results: github.com/Mohsin2686/prompt-bench The….
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that over two weeks, I built a small evaluation harness to test whether popular prompting techniques — few-shot examples, Chain-of-Thought, self-consistency voting, Tree-of-Thought — actually improve accuracy, and at what cost.
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