MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension. MedGemma 4B utilizes a SigLIP image encoder that has been specifically pre-trained on a variety of de-identified medical data, including chest X-rays, dermatology images, ophthalmology images, and histopathology slides. Its LLM component is trained on a diverse set of medical data, including radiology images, histopathology patches, ophthalmology images, and dermatology images. MedGemma is a multimodal model primarily evaluated on single-image tasks. It has not been evaluated for multi-turn applications and may be more sensitive to specific prompts than its predecessor, Gemma 3. Developers should consider bias in validation data and data contamination concerns when using MedGemma.
Benchmarks
评测成绩
| 评测基准 | 类别 | 分数 | 来源 |
|---|---|---|---|
| MIMIC CXR | healthcare vision multimodal | 88.9 | 来源 |
| DermMCQA | healthcare | 71.8 | 来源 |
| PathMCQA | healthcare vision multimodal reasoning | 69.8 | 来源 |
| SlakeVQA | vision healthcare multimodal reasoning | 62.3 | 来源 |
| VQA-Rad | vision healthcare multimodal | 49.9 | 来源 |
| CheXpert CXR | healthcare vision | 48.1 | 来源 |
| MedXpertQA | healthcare reasoning multimodal | 18.8 | 来源 |
Pricing
API 价格对比
暂无 API 价格。