LM Studio

LM Studio runs open-source models locally through a desktop app with an OpenAI-compatible local server. LM Studio supports multiple open-source models. See the library here. We recommend experimenting to find the best-suited model for your use case. Here are some general recommendations:

llama3.3 models are good for most basic use cases.
qwen models perform specifically well with tool use.
deepseek-r1 models have strong reasoning capabilities.
phi4 models offer strong performance at a small size.

Set up a model

Install LM Studio, download the model you want to use, and run it.

Example

After you have the model locally, use the LMStudio model class to access it. It uses the OpenAI client, so install the openai package:

uv pip install -U openai agno

from agno.agent import Agent
from agno.models.lmstudio import LMStudio

agent = Agent(
    model=LMStudio(id="qwen2.5-7b-instruct-1m"),
    markdown=True
)

# Print the response in the terminal
agent.print_response("Share a 2 sentence horror story.")

View more examples here.

Params

Parameter	Type	Default	Description
`id`	`str`	`"qwen2.5-7b-instruct-1m"`	The id of the LMStudio model to use
`name`	`str`	`"LMStudio"`	The name of the model
`provider`	`str`	`"LMStudio"`	The provider of the model
`api_key`	`Optional[str]`	`"not-provided"`	The API key for LMStudio (usually not needed for local)
`base_url`	`str`	`"http://127.0.0.1:1234/v1"`	The base URL for the local LMStudio server

LMStudio is a subclass of the OpenAILike class and has access to the same params.

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Set up a model

Example

Params

​Set up a model

​Example

​Params

Set up a model

Example

Params