MiniMaxAI's SynLogic-Mix-3-32B is a 32 billion parameter multi-domain reasoning model built on Qwen2.5-32B-Base. It is trained using Zero-RL (reinforcement learning from scratch) on a diverse mixture of logical reasoning, mathematical, and coding data. This model excels at complex reasoning tasks, demonstrating superior cross-domain transfer and outperforming similar models on benchmarks like BBEH and GPQA-Diamond. It is optimized for applications requiring robust logical, mathematical, and coding problem-solving capabilities.
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SynLogic-Mix-3-32B: Multi-Domain Reasoning Model
SynLogic-Mix-3-32B, developed by MiniMaxAI, is an advanced 32 billion parameter model based on Qwen2.5-32B-Base. It stands out due to its unique Zero-RL (reinforcement learning from scratch) training methodology, applied to a diverse dataset encompassing logical reasoning, mathematics, and coding tasks. This approach enables the model to achieve enhanced generalization and superior cross-domain transfer compared to single-domain training.
Key Capabilities & Features
- Multi-Domain Training: Jointly trained on 35k mathematical, 9k coding, and 17k SynLogic logical reasoning samples.
- Zero-RL Training: Utilizes Group Relative Policy Optimization (GRPO) from a base model, without instruction tuning.
- Enhanced Generalization: Demonstrates improved performance across various reasoning domains.
Performance Highlights
SynLogic-Mix-3-32B shows strong performance on challenging benchmarks:
- BBEH: Achieves 28.6, matching or surpassing DeepSeek-R1-Distill-Qwen-32B.
- KOR-Bench: Scores 65.0, comparable to leading models.
- GPQA-Diamond: Outperforms DeepSeek-R1-Zero-Qwen-32B by +2.5 points, scoring 57.5.
- Ablation studies confirm that the inclusion of SynLogic logical reasoning data significantly boosts performance on logical reasoning (e.g., +10.1 points on BBEH) and out-of-domain reasoning tasks.
Ideal Use Cases
This model is particularly well-suited for applications requiring robust performance in:
- Complex Logical Reasoning: Solving intricate logical puzzles and problems.
- Mathematical Problem Solving: Handling diverse mathematical queries and computations.
- Code Generation & Understanding: Assisting with coding tasks and understanding programming logic.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.