prithivMLmods/Logics-Qwen3-Math-4B

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Oct 14, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The prithivMLmods/Logics-Qwen3-Math-4B is a 4 billion parameter Qwen3-based model fine-tuned for advanced mathematical reasoning and logical coding. Developed by prithivMLmods, it excels in structured mathematical problem-solving, algorithmic logic, and probabilistic reasoning. This model is optimized for high-precision math and logic tasks, making it suitable for educators, researchers, and developers in computational logic. It supports structured output formats like LaTeX and JSON, and is deployable on mid-range GPUs due to its efficient 4B parameter footprint.

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Logics-Qwen3-Math-4B: Specialized Reasoning Model

Logics-Qwen3-Math-4B, developed by prithivMLmods, is a 4 billion parameter model built upon the Qwen3 architecture. It is specifically fine-tuned on OpenMathReasoning, OpenCodeReasoning, and Helios-R-6M datasets to excel in mathematical reasoning and logical coding tasks. This model is designed for high-precision problem-solving, algorithmic logic, and probabilistic reasoning.

Key Capabilities

  • Mathematical & Logical Reasoning: Optimized for complex math, algorithmic problem-solving, and logical coding.
  • Event-Driven & Probabilistic Modeling: Capable of probability-based simulations and multi-step logical reasoning.
  • Multilingual Support: Handles math and logic tasks across various languages.
  • Hybrid Symbolic-Algorithmic Thinking: Combines structured logic with symbolic computation and probabilistic inference.
  • Structured Output: Generates outputs in formats like LaTeX, Markdown, JSON, CSV, and YAML for seamless integration.
  • Optimized Footprint: Its 4B parameters allow deployment on mid-range GPUs, offline clusters, and edge devices while maintaining high reasoning quality.

Ideal Use Cases

  • High-precision mathematical reasoning and problem-solving.
  • Algorithmic logic, structured coding tasks, and probability analysis.
  • Educational and research workflows requiring computational logic.
  • Deployment in resource-constrained environments.
  • Generation of structured data and technical content.