FreedomIntelligence/HuatuoGPT-3-9B

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 17, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

HuatuoGPT-3-9B by FreedomIntelligence is a 9 billion parameter medical large language model built on Qwen3.5-9B, specifically adapted for medical reasoning. It utilizes a novel One-stage Policy Optimization (OnePO) method, directly applying reinforcement learning without prior domain-specific supervised fine-tuning. This model is designed to provide medical insights and requires a 'thinking mode' for inference, generating reasoning before its final answer.

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HuatuoGPT-3-9B: Medical Reasoning LLM

HuatuoGPT-3-9B, developed by FreedomIntelligence, is a 9 billion parameter medical large language model based on the Qwen3.5-9B architecture. Its core innovation lies in the One-stage Policy Optimization (OnePO) method, which directly adapts the language model to the medical domain using reinforcement learning. This approach bypasses traditional supervised fine-tuning stages, making it a distinct method for domain adaptation.

Key Capabilities & Features

  • Specialized Medical Reasoning: Designed specifically for complex medical queries and diagnostic support.
  • OnePO Training: Leverages a unique reinforcement learning strategy for domain adaptation, guided by teacher responses that are phased out as the model improves.
  • Thinking Mode Inference: Requires enable_thinking=True during inference, allowing the model to generate internal reasoning steps before producing its final medical answer.
  • Open-source Resources: FreedomIntelligence provides the training code, a medical RL dataset, and an 8B rubric grader for further research and development.

When to Use This Model

  • Medical Question Answering: Ideal for applications requiring detailed and reasoned responses to medical inquiries.
  • Research in Medical AI: Useful for researchers exploring novel domain adaptation techniques, particularly OnePO.
  • Clinical Decision Support Systems: Can serve as a component in systems that require robust medical reasoning capabilities.