Aurora-Gem/OptMATH-Qwen2.5-7B

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jan 5, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Aurora-Gem/OptMATH-Qwen2.5-7B is a 7.6 billion parameter language model based on the Qwen2.5 architecture. This model is specifically optimized for mathematical reasoning and problem-solving tasks. It is designed to provide accurate and efficient solutions for complex quantitative challenges, making it suitable for applications requiring strong numerical and logical capabilities.

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Aurora-Gem/OptMATH-Qwen2.5-7B Overview

Aurora-Gem/OptMATH-Qwen2.5-7B is a specialized 7.6 billion parameter language model built upon the robust Qwen2.5 architecture. Its core distinction lies in its fine-tuning and optimization for mathematical reasoning and quantitative problem-solving. With a context length of 32768 tokens, it is equipped to handle intricate mathematical expressions and multi-step logical deductions.

Key Capabilities

  • Advanced Mathematical Reasoning: Excels at interpreting and solving a wide range of mathematical problems, from algebra to calculus.
  • Logical Deduction: Capable of following complex logical chains to arrive at correct numerical or symbolic answers.
  • Qwen2.5 Foundation: Benefits from the strong base capabilities of the Qwen2.5 model family, ensuring general language understanding alongside its mathematical prowess.

Good For

  • Educational Tools: Assisting students with homework, explaining mathematical concepts, or generating practice problems.
  • Scientific Research: Processing and analyzing numerical data, performing calculations, or validating mathematical models.
  • Quantitative Analysis: Applications requiring precise numerical outputs and logical consistency, such as financial modeling or engineering simulations.
  • Automated Problem Solving: Developing systems that can autonomously tackle mathematical challenges.