FreedomIntelligence releases HuatuoGPT-3 multimodal model on Hugging Face
The model builds on Qwen3.8-27B with a reinforcement-learning method called One-stage Policy Optimization (OnePO). It requires a thinking mode during inference, generating reasoning before final answers, and supports image-text-to-text tasks.
Key points
- HuatuoGPT-3 uses OnePO to adapt language models to medical tasks without supervised fine-tuning
- Model requires *enablethinking=True* for reasoning before final answers, with a </think> delimiter
- Open-source on Hugging Face with training data, code, and an 8B rubric grader released
The model’s training code, medical reinforcement-learning dataset, and an 8B rubric grader are also open. Users can deploy it via vLLM or SGLang or run it locally with Docker. Example prompts include medical queries like ‘What are the common causes of chest pain?’ or image descriptions. No performance benchmarks or context window size are provided.
FreedomIntelligence/HuatuoGPT-3-27B · Hugging Face
huggingface.co · 24 September 2026
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