Skip to main content
Meta offers a suite of powerful multi-modal language models known for their strong performance across a wide range of tasks, including superior text understanding and visual intelligence. We recommend experimenting to find the best-suited model for your use-case. Here are some general recommendations:
  • Llama-4-Scout-17B: Excellent performance for most general tasks, including multi-modal scenarios.
  • Llama-3.3-70B: Powerful instruction-following model for complex reasoning tasks.
Explore all the models here.

​
Authentication

Set your LLAMA_API_KEY environment variable: 
bash Mac export LLAMA_API_KEY=YOUR_API_KEY  bash Windows setx     LLAMA_API_KEY YOUR_API_KEY

​
Example

Use Llama with your Agent: 
from agno.agent import Agent
from agno.models.meta import Llama

agent = Agent(
model=Llama(
id="Llama-4-Maverick-17B-128E-Instruct-FP8",
),
markdown=True
)

agent.print_response("Share a 2 sentence horror story.")
View more examples here.

​
Parameters

ParameterTypeDefaultDescription
idstr"meta-llama/Meta-Llama-3.1-405B-Instruct"The id of the Meta model to use
namestr"MetaLlama"The name of the model
providerstr"Meta"The provider of the model
api_keyOptional[str]NoneThe API key for Meta (defaults to META_API_KEY env var)
base_urlstr"https://api.llama-api.com"The base URL for the Meta API

​
OpenAI-like Parameters

LlamaOpenAI supports all parameters from OpenAI Like.

​
Resources

⌘I