Reddit Tries Recursive Meta-Prompting to Cut Qwen's Thinking Tokens by Half
Rare_Potential_1323 · reddit · 2026-08-21
A Reddit post explores using Recursive Meta-Prompting (RMP) on a 27B Qwen model to compress reasoning overhead, with two prompt recipes.
Recipe 1: adaptive reasoning tiers — a system prompt defining three levels: Direct Path (factual retrieval, simple code, low-ambiguity requests skip <think> entirely), Bounded Thinking (multi-step logic, debugging, math limited to a 3-point checklist: state constraints, execute stepwise, verify edge cases), and Deep Thinking (reserved for proofs, complex design, high ambiguity), plus a self-correction rule to collapse if internal reasoning exceeds 150 tokens on routine queries.
Recipe 2: self-written prompt — ask the model to analyze its own dual thinking/instruct modes and generate a token-efficiency governor system prompt that decides when to bypass internal monologue versus trigger bounded reasoning, targeting a 50%+ cut in thinking tokens on routine queries while preserving benchmark accuracy.
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