Intern-Decision 多模态决策模型对标 Jev
0.8B/2B/4B 三档模型在七项决策基准上平均 79.38/84.68/90.02，4B 以 88.74 超过 Jev 的 88.74 并延迟更低，单次前向输出结构化 JSON 与校准概率。
Intern-Decision scales multimodal structured decision-making across 0.8B, 2B, and 4B models. 🤖 https://modelscope.ai/collections/Shanghai_AI_Laboratory/Intern-Decision 🏆 The three models average 79.38, 84.68, and 90.02 across seven decision benchmarks. Intern-Decision-4B surpasses Jev at 88.74 while achieving better probability calibration. ⚡ Reported mean latency is 33.98 ms, 33.28 ms, and 44.16 ms respectively, compared with 109.70 ms for Jev in the same local HF setup. 🧠 One forward pass answers multiple choice, score, and yes/no questions with typed JSON and calibrated probability distributions. 🖼️ Text states and up to eight images enable routing, tool selection, scoring, and multimodal workflow control. 📜 Apache 2.0. Applicable Qwen3.5 upstream notices must be retained.