Compatible Google Models
You can import large language models from Hugging Face and OCI Object Storage buckets into OCI Generative AI, create endpoints for those models, and use them in the Generative AI service.
MedGemma
Google MedGemma 27B Text IT is a 27-billion-parameter language model based on the Gemma 3 architecture. Trained on medical literature and clinical records, the model is instruction-tuned (IT), enabling it to better follow user requests and help perform healthcare-focused tasks such as medical question answering, clinical support, and summarizing.
| Hugging Face Model ID | Model Capability | Recommended Dedicated AI Cluster Unit Shape |
|---|---|---|
| google/medgemma-27b-text-it | TEXT_TO_TEXT |
|
Gemma
| Hugging Face Model ID | Model Capability | Recommended Dedicated AI Cluster Unit Shape |
|---|---|---|
| google/gemma-4-31B-it | IMAGE_TEXT_TO_TEXT |
|
| google/gemma-3-4b-it | IMAGE_TEXT_TO_TEXT | A100_80G_X1 |
| google/gemma-3-270m-it | TEXT_TO_TEXT | A100_80G_X1 |
| google/gemma-3-27b-it | IMAGE_TEXT_TO_TEXT | A100_80G_X2 |
| google/gemma-3-12b-it | IMAGE_TEXT_TO_TEXT | A100_80G_X1 |
| google/gemma-3-1b-it | TEXT_TO_TEXT | A100_80G_X1 |
| google/gemma-2-9b-it | TEXT_TO_TEXT | A100_80G_X1 |
| google/gemma-2-27b-it | TEXT_TO_TEXT | A100_80G_X2 |
| google/gemma-2-2b-it | TEXT_TO_TEXT | A100_80G_X1 |
Important
- For imported models, you can use the native context length specified by the model provider. However, the effective maximum context length is limited by the underlying hardware setup that you select for the hosting dedicated AI clusters in OCI Generative AI. To take full advantage of a model's native context length, you might need to provision more hardware resources.
- Use the fine-tuned models only if they match the compatible base model's transformer version and have a parameter count within ±10% of the original.
- For available hardware and steps on how to deploy the imported models, see Managing Imported Models.