FreedomIntelligence/HuatuoGPT-3-32B

Hugging Face
TEXT GENERATIONConcurrent Unit Cost:2Model Size:32BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Mar 20, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Warm

HuatuoGPT-3-32B is a 32 billion parameter medical Large Language Model developed by FreedomIntelligence. It is built on the Qwen3-32B backbone and specialized for medical applications using SeedRL, an RL-only domain adaptation paradigm. This model excels at medical question answering and reasoning, providing responses with an explicit reasoning block. It is designed for direct inference in medical contexts.

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HuatuoGPT-3-32B: A Specialized Medical LLM

HuatuoGPT-3-32B, developed by FreedomIntelligence, is a 32 billion parameter medical Large Language Model. It is built upon the Qwen3-32B backbone and uniquely adapted for the medical domain through SeedRL, an innovative RL-only domain adaptation paradigm. This method transforms a general-purpose base model into a medical expert in a single reinforcement learning stage.

Key Capabilities & Features

  • Medical Specialization: Specifically trained and optimized for medical applications, making it suitable for complex medical queries and reasoning.
  • SeedRL Training: Utilizes a novel RL-only domain adaptation approach for efficient and effective specialization.
  • Reasoning Mode: By default, the model operates in a "thinking mode," providing a <think>...</think> reasoning block before its final response, enhancing transparency and interpretability.
  • Open-Source: Part of the HuatuoGPT-3 family, which includes other models like HuatuoGPT-3-8B (based on Qwen3-8B-Base) and HuatuoGPT-3-7B-Pangu (based on openPangu-Embedded-7B).

Good For

  • Medical Question Answering: Ideal for scenarios requiring accurate and context-aware responses to medical questions.
  • Clinical Decision Support: Can assist in providing preliminary considerations for patient symptoms.
  • Research and Development: Useful for researchers exploring domain adaptation techniques and medical LLM performance.

This model is designed for direct inference and can be deployed using standard LLM tools like vLLM or SGLang, similar to its base model, Qwen3-32B.