MiniCPM5-2B-Jev Decision Model Released: 78.79% on JevBench
Developer ActbroDev built the System 1 decision model MiniCPM5-2B-Jev based on OpenBMB's MiniCPM5-2B. After inputting a document and a question, it directly returns the probabilities of predefined options rather than generating free text. The project reports that it scores 78.79% on JevBench, ranking first among ≤2B open-weight System 1 / Jev models, with 86.41% accuracy on the decision-v7 benchmark and an ECE of 0.0307. The code, LoRA adapters, and calibration head are open-sourced under Apache 2.0, and it provides a /v1/systemone structured decision API and shared-context KV-cache reuse.
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What if your model could make a structured choice instead of writing another paragraph? 🎯
Developer @ActbroDev built MiniCPM5-2B-Jev on OpenBMB’s MiniCPM5-2B, adapting it into a System 1 decision model.
📄 Give it a document and a set of questions. It returns probabilities for predefined options, without generating a free-form answer—helping developers: - Classify requests and route support tickets - Check whether conditions or requirements are met - Score cases against defined criteria
📊 Results reported by the project: 🏆 78.79% on JevBench, ranking #1 among ≤2B open-weight System 1 / Jev models ✅ 86.41% accuracy on the 10-source decision-v7 benchmark 📏 0.0307 ECE on decision-v7, measuring how closely confidence matches accuracy
🛠️ Built for developers: • Structured decision API via /v1/systemone • Shared-context KV-cache reuse across multiple questions • Open-source code, LoRA adapters, and calibration head under Apache 2.0 • Training and evaluation scripts to explore and reproduce the approach
From support-ticket routing to criteria-based scoring, this project shows how the community is adapting MiniCPM for practical decision workflows. 🌍
🙌 Shout-out to yuting-ai for building and sharing!
🔗 Explore Project: https://t.co/VRkkO4cY7G 🤗 Get MiniCPM5-2B: https://t.co/TNUu629lXn
#MiniCPM #OpenBMB #OpenSourceAI