Get Better Answers by Comparing Multiple Reasoning Chains

Guide the user through using dspy.MultiChainComparison to improve answer quality. Instead of relying on a single chain of thought, you generate several independent reasoning chains yourself and then hand them to this module, which selects the best final answer by comparing them.

Step 1 — Gather context

Before generating code, clarify:

1. What is your signature? What inputs does your task take and what output do you want? (example: "problem -> recommendation" or a class-based dspy.Signature)
2. How many chains (M)? Start with M=3 unless latency or cost is constrained. Increase to M=5 for high-stakes tasks where you have evidence that a single ChainOfThought is unreliable.
3. Are you wrapping in a dspy.Module? Wrapping both the generator and the comparison step in a module enables optimizer tuning of both prompts.
4. Do you need selective routing? If only some inputs are complex enough to warrant MultiChainComparison, an adaptive router (classify difficulty → fast CoT or multi-chain) reduces cost significantly.

What is MultiChainComparison

dspy.MultiChainComparison is a DSPy module that: