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Open Reasoner Zero 32B

Developed by Open-Reasoner-Zero
The first open-source implementation of large-scale reasoning-oriented reinforcement learning focusing on scalability, simplicity, and ease of use
Downloads 498
Release Time : 2/18/2025

Model Overview

Open Reasoner Zero is an open-source solution for reinforcement learning based on foundational model scaling, focusing on enhancing reasoning capabilities, suitable for high-difficulty tasks such as mathematical reasoning.

Model Features

Scalable Reinforcement Learning
Supports model training from 500M to 32B parameters, demonstrating consistent scaling capabilities
Efficient Training
Achieves or surpasses the performance of similar models with only one-tenth of the training steps
Complete Open-source
Publicly available source code, parameter settings, training data, and model weights
Resource Optimization
Provides single-GPU training solutions, lowering the research barrier

Model Capabilities

Mathematical problem solving
Complex reasoning
Multi-step problem answering
High-difficulty competition problem solving

Use Cases

Education
Math Competition Problem Solving
Solving math competition problems such as AIME
Achieved 48% accuracy on AIME2024
Math Learning Assistance
Provides step-by-step math problem solving
Research
Reinforcement Learning Research
Serves as a benchmark model for scalable reinforcement learning
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