Model Overview

mR3-Qwen3-4B-en-prompt-en-thinking is a 4 billion parameter reward model, developed by rubricreward, and is a member of the mR3 (Multilingual Rubric-Agnostic Reward Reasoning Models) family. This model is fine-tuned from the Qwen3-4B base model and specializes in evaluating AI-generated responses. It leverages a curated mR3 dataset spanning 72 languages, which includes instructions, task descriptions, inputs, responses, evaluation rubrics, scores, and corresponding reasoning.

Key Capabilities

• Multilingual Evaluation: Trained on data from 72 languages, enabling broad application.
• Rubric-Agnostic Reasoning: Provides scores and detailed reasoning for AI responses based on defined rubrics.
• Task Versatility: Supports various tasks including classification, preference optimization, and question answering.
• Detailed Feedback: Generates an explanation and a verdict (Assistant A or Assistant B) based on factors like safety, helpfulness, relevance, conciseness, politeness, and coverage.

Use Cases

• Automated Content Moderation: Assessing the safety and appropriateness of generated text.
• AI Response Quality Assurance: Evaluating the helpfulness and relevance of AI outputs.
• Preference Optimization: Providing structured feedback for training and refining other language models.
• Research in Reward Modeling: A foundational model for exploring multilingual and rubric-based reward mechanisms, as detailed in their paper.

This model is licensed under Apache 2.0 and can be efficiently used with transformers or vLLM for inference.