Oracle Cloud Infrastructure Documentation

Supported Meta Models

You can import large language models from Hugging Face and models imported from an OCI Object Storage bucket into OCI Generative AI, create endpoints for those models, and use them in the Generative AI service.

These models are an improved version of Meta Llama models with Grouped Query Attention (GQA). For more information, see Llama 2, Llama 3, Llama 3.1, Llama 3.2, Llama 3.3, Llama 4 in the Hugging Face documentation.

Meta Llama

Supported Meta Llama Models
Hugging Face Model ID Model Capability Recommended Dedicated AI Cluster Unit Shape
meta-llama/Llama-2-7b-chat-hf TEXT_TO_TEXT A100_80G_X1
meta-llama/Llama-2-13b-chat-hf TEXT_TO_TEXT A100_80G_X1
meta-llama/Llama-2-70b-chat-hf TEXT_TO_TEXT A100_80G_X4
meta-llama/Meta-Llama-3-8B-Instruct TEXT_TO_TEXT A100_80G_X1
meta-llama/Meta-Llama-3-70B-Instruct TEXT_TO_TEXT A100_80G_X4
meta-llama/Llama-3.1-8B-Instruct TEXT_TO_TEXT A100_80G_X1
meta-llama/Llama-3.1-70B-Instruct TEXT_TO_TEXT A100_80G_X4
meta-llama/Llama-3.1-405B-Instruct-FP8 TEXT_TO_TEXT H100_X8
meta-llama/Llama-3.2-1B-Instruct TEXT_TO_TEXT A100_80G_X1
meta-llama/Llama-3.2-3B-Instruct TEXT_TO_TEXT A100_80G_X1
meta-llama/Llama-3.2-11B-Vision-Instruct IMAGE_TEXT_TO_TEXT A100_80G_X1
RedHatAI/Llama-3.2-90B-Vision-Instruct-FP8-dynamic IMAGE_TEXT_TO_TEXT H100_X4
meta-llama/Llama-3.3-70B-Instruct TEXT_TO_TEXT A100_80G_X4
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 IMAGE_TEXT_TO_TEXT H100_X8
meta-llama/Llama-4-Scout-17B-16E-Instruct IMAGE_TEXT_TO_TEXT H100_X4
Note

  • To import a fine-tuned version of a model, only fine-tuned models that use the same transformers version as the original model and have a parameter count within ±10% of the original are supported.
  • If the instance type for the recommended unit shape isn’t available in your region, select a higher-tier instance (for example, select an H100 shape instead of an A100-80G shape).
  • For prerequisites and how to import models, see Managing Imported Models (New).