This paper presents the participation of team PSL in the QIAS 2026 Shared Task on Arabic Islamic inheritance reasoning. The task evaluates the ability of large language models to solve inheritance cases that require legal interpretation, multi-step reasoning, and precise numerical computation. We compare \textit{commercial} and \textit{open-source} models under a unified prompting strategy to assess their effectiveness in structured legal reasoning with minimal task-specific adaptation. \\ Our results show a clear gap in reliability between the two model families. Commercial models demonstrate stronger performance in identifying eligible heirs, applying exclusion rules, and maintaining consistency across reasoning steps. In contrast, open-source models exhibit greater instability, particularly in cases involving dependent legal decisions and fractional share adjustments. The best performance is achieved by \textit{Gemini 2.5 Flash}, with an MRE of $0.989$.

翻译：本文介绍了PSL团队参与2026年阿拉伯伊斯兰继承推理共享任务的成果。该任务评估大语言模型在需要进行法律解释、多步推理和精确数值计算的继承案例中的解决能力。我们在统一提示策略下比较了商业模型和开源模型，评估其在最小化任务特定适配情况下进行结构化法律推理的有效性。研究结果揭示了两种模型家族在可靠性上的显著差距：商业模型在识别合法继承人、应用排除规则以及保持推理步骤一致性方面表现更优；而开源模型则表现出更大的不稳定性，特别是在涉及依赖法律判决和分数份额调整的案例中。性能最优的模型为Gemini 2.5 Flash，其MRE达到0.989。