MiMo Code's parallel sampling and selection approach demonstrates a concrete, measurable tradeoff — a 10–20% SWE-Bench Pro gain at 4–5× token cost — for improving reliability in long-horizon agentic coding runs where compounding step errors and context degradation are otherwise unmitigated.