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azure/llama (Azure Llama Models)
This example demonstrates how to use Meta Llama models on Azure AI Foundry with promptfoo.
You can run this example with:
npx promptfoo@latest init --example azure/llama
cd azure/llama
Setup
- Deploy Llama models in Azure AI Foundry
- Set your environment variables:
export AZURE_API_KEY=your-api-key
export AZURE_API_HOST=your-deployment.services.ai.azure.com
Available Llama Models
| Model | Description |
|---|---|
Llama-4-Maverick-17B-128E-Instruct-FP8 |
Llama 4 Maverick (128 experts, FP8) |
Llama-4-Scout-17B-16E-Instruct |
Llama 4 Scout (16 experts) |
Llama-3.3-70B-Instruct |
Llama 3.3 70B |
Meta-Llama-3.1-405B-Instruct |
Llama 3.1 405B |
Meta-Llama-3.1-70B-Instruct |
Llama 3.1 70B |
Meta-Llama-3.1-8B-Instruct |
Llama 3.1 8B |
Running the Example
npx promptfoo@latest eval
npx promptfoo@latest view
Configuration
The example compares Llama 4 Maverick and Llama 4 Scout on code generation tasks. This helps evaluate the trade-off between model capacity (expert count), speed, and quality.