GLM-Z1-9B-0414: A Compact Reasoning Powerhouse

GLM-Z1-9B-0414 is a 9 billion parameter model from the GLM family, developed by THUDM. It is a smaller-scale variant of the GLM-4-32B-0414 series, which is pre-trained on 15T of high-quality data, including extensive reasoning-type synthetic data. This model is specifically enhanced for deep thinking capabilities through cold start and extended reinforcement learning, with further training on mathematics, code, and logic tasks.

Key Capabilities

Advanced Mathematical Reasoning: Significantly improves mathematical abilities and complex task-solving compared to base models.
General Reinforcement Learning: Incorporates pairwise ranking feedback to enhance overall general capabilities.
Efficient Deployment: Offers an excellent balance between efficiency and effectiveness, making it suitable for resource-constrained scenarios.
Enforced Thinking: Supports a mechanism to ensure the model 'thinks' before responding, improving output quality.
Long Context Handling: Can utilize YaRN (Rope Scaling) for contexts exceeding 8,192 tokens, extending up to 32,768 tokens.

Good For

Applications requiring strong mathematical and logical problem-solving.
Scenarios where efficient, lightweight deployment is critical without sacrificing reasoning performance.
Tasks benefiting from enforced thinking processes to generate more deliberate responses.
Complex agent tasks, instruction following, and engineering code generation where atomic capabilities are crucial.