What are Open Source LLMs for Medical Industry?
Open source large language models for the medical industry are specialized AI systems trained to understand, process, and generate medical content with high accuracy and safety standards. These models can assist with clinical documentation, medical research, diagnostic support, patient communication, and medical education. They incorporate advanced reasoning capabilities to handle complex medical scenarios while maintaining compliance with healthcare regulations. Open source medical LLMs democratize access to powerful healthcare AI tools, enabling hospitals, research institutions, and healthcare startups to develop innovative solutions for patient care and medical research.
OpenAI GPT-OSS-120B
GPT-OSS-120B is OpenAI's open-weight large language model with ~117B parameters (5.1B active), using a Mixture-of-Experts (MoE) design and MXFP4 quantization to run on a single 80 GB GPU. It delivers o4-mini-level or better performance in reasoning, coding, health, and math benchmarks, with full Chain-of-Thought (CoT), tool use, and Apache 2.0-licensed commercial deployment support.
OpenAI GPT-OSS-120B: Enterprise-Grade Medical AI
GPT-OSS-120B is OpenAI's open-weight large language model with ~117B parameters (5.1B active), using a Mixture-of-Experts (MoE) design and MXFP4 quantization to run on a single 80 GB GPU. It delivers o4-mini-level or better performance in reasoning, coding, health, and math benchmarks, with full Chain-of-Thought (CoT), tool use, and Apache 2.0-licensed commercial deployment support. This makes it ideal for healthcare applications requiring robust reasoning capabilities and reliable performance in medical contexts.
Pros
- Excellent performance on health and medical benchmarks.
- Apache 2.0 license enables commercial healthcare deployment.
- Efficient MoE architecture reduces computational costs.
Cons
- Requires 80 GB GPU for optimal performance.
- May need medical-specific fine-tuning for specialized applications.
Why We Love It
- It combines OpenAI's proven architecture with healthcare-focused performance and commercial licensing, making it perfect for enterprise medical AI applications.
GLM-4.5V
GLM-4.5V is the latest generation vision-language model (VLM) released by Zhipu AI. Built upon the flagship text model GLM-4.5-Air with 106B total parameters and 12B active parameters, it utilizes a MoE architecture for superior multimodal performance. With innovations like 3D-RoPE and a 'Thinking Mode' switch, it excels at processing medical images, videos, and documents—achieving state-of-the-art performance on multimodal benchmarks.
GLM-4.5V: Advanced Medical Imaging and Document Analysis
GLM-4.5V is the latest generation vision-language model (VLM) released by Zhipu AI. The model is built upon the flagship text model GLM-4.5-Air, which has 106B total parameters and 12B active parameters, and it utilizes a Mixture-of-Experts (MoE) architecture to achieve superior performance at a lower inference cost. With innovations like 3D Rotated Positional Encoding (3D-RoPE) and a 'Thinking Mode' switch, it's ideal for medical imaging analysis, processing diverse visual content such as medical images, videos, and long documents while achieving state-of-the-art performance among open-source models on multimodal benchmarks.
Pros
- Excellent for medical imaging and document analysis.
- Thinking Mode provides detailed medical reasoning.
- Cost-effective MoE architecture for healthcare deployment.
Cons
- Shorter context length compared to text-only models.
- Requires specialized hardware for vision processing.
Why We Love It
- It uniquely combines advanced vision-language capabilities with medical reasoning, making it ideal for radiology, pathology, and clinical document analysis applications.
DeepSeek-R1
DeepSeek-R1 is a reasoning model powered by reinforcement learning (RL) with 671B total parameters in a MoE architecture. Optimized to address repetition and readability issues, it incorporates cold-start data for enhanced reasoning performance. It achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks—making it ideal for complex medical reasoning and clinical decision support.
DeepSeek-R1: Advanced Clinical Reasoning Powerhouse
DeepSeek-R1 is a reasoning model powered by reinforcement learning (RL) that addresses the issues of repetition and readability. With 671B total parameters in a MoE architecture, it incorporates cold-start data to optimize reasoning performance. It achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks, making it exceptional for complex medical reasoning scenarios, clinical decision support, and medical research applications that require careful step-by-step analysis.
Pros
- Exceptional reasoning capabilities for complex medical scenarios.
- Massive 671B parameter capacity for comprehensive medical knowledge.
- 164K context length for processing long medical documents.
Cons
- High computational requirements due to large parameter count.
- Higher inference costs compared to smaller models.
Why We Love It
- It delivers unmatched reasoning capabilities for complex medical scenarios, making it the go-to choice for advanced clinical decision support and medical research applications.
Medical AI Model Comparison
In this table, we compare 2025's leading open source LLMs for medical applications, each with unique strengths for healthcare use cases. For enterprise medical deployment, OpenAI GPT-OSS-120B provides robust health benchmark performance with commercial licensing. For medical imaging and document analysis, GLM-4.5V offers advanced vision-language capabilities. For complex clinical reasoning, DeepSeek-R1 delivers unmatched analytical depth. This comparison helps you choose the right model for your specific medical AI application.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | OpenAI GPT-OSS-120B | OpenAI | Medical Reasoning | $0.09 input / $0.45 output per M tokens | Health benchmark excellence |
| 2 | GLM-4.5V | Zhipu AI | Medical Vision-Language | $0.14 input / $0.86 output per M tokens | Medical imaging analysis |
| 3 | DeepSeek-R1 | DeepSeek AI | Medical Reasoning | $0.5 input / $2.18 output per M tokens | Advanced clinical reasoning |
Frequently Asked Questions
Our top three picks for medical applications in 2025 are OpenAI GPT-OSS-120B, GLM-4.5V, and DeepSeek-R1. Each of these models stood out for their medical performance, safety considerations, and unique approach to solving challenges in healthcare AI applications.
For enterprise medical deployment requiring health benchmark performance, OpenAI GPT-OSS-120B is ideal. For medical imaging analysis, radiology, and pathology applications, GLM-4.5V excels with its vision-language capabilities. For complex clinical decision support and medical research requiring deep reasoning, DeepSeek-R1 is the top choice.