Comparison
Reflexion vs Self-Consistency
Reflexion and Self-Consistency are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Reflexion
Multi-attempt agents on verifiable tasks (code, math, structured outputs). Less useful for one-shot tasks.
A coding agent that gets a test failure, generates a reflection ("the function signature expects a list, I passed a string"), and retries with the corrected understanding.
When you would reach for Self-Consistency
When the task has a verifiable answer (math, logic, code that compiles) and N× compute is acceptable.
A GSM8K eval: sample 32 CoT completions per problem, take the majority numeric answer.
Frequently asked
What is the difference between Reflexion and Self-Consistency?
Reflexion: Reflexion is a pattern where an agent runs, observes failures, generates a short natural-language "reflection" on what went wrong, and retries with that reflection appended to its prompt — improving via self-critique without weight updates. Self-Consistency: Self-consistency samples N chain-of-thought completions for the same problem and takes the majority answer. Improves accuracy on math and reasoning tasks at N× the cost.
When should I use Reflexion vs Self-Consistency?
Multi-attempt agents on verifiable tasks (code, math, structured outputs). Less useful for one-shot tasks. When the task has a verifiable answer (math, logic, code that compiles) and N× compute is acceptable.
Are Reflexion and Self-Consistency the same thing?
No. Reflexion is agents & tools; Self-Consistency is prompting. They are related but address different parts of the AI stack.