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Run and Deploy Models

This guide explains how to use run to run models and load to deploy them.

Downloading a model only stores its files locally. Before inference can begin, LlamaPi must load the model onto the appropriate inference platform and create a runtime model that can receive requests. A loaded model consumes memory resources on the device.

Both run and load load a model, but they serve different purposes and have different lifecycles:

MethodBehaviorUse case
llamapi runStarts the service, downloads, and loads the model as needed; unloads a model newly loaded by the command when it exitsInteractive chats and single prompts
llamapi loadLoads a downloaded model; keeps it deployed after the command exits until it is unloaded or the service stopsOngoing API service and third-party application integration

If run reuses a model already deployed with load, exiting run does not unload that model.

Run a Model (run)​

The run command automatically finds, downloads when necessary, and loads the model before opening an interactive chat or processing a single prompt.

Open an interactive chat:

llamapi run qwen3:4b

Send a single prompt:

llamapi run qwen3:4b "Explain what an NPU is."

Set a system prompt and open an interactive chat:

llamapi run qwen3:4b --system "You are an embedded Linux engineer."

When run exits, it automatically unloads a model newly loaded by that command, so the model can no longer receive API requests. Use load if the model must remain available.

Use Interactive Mode​

The following commands are available in interactive mode:

CommandDescription
/helpShow available commands
/clearClear conversation history
/system <prompt>Set or clear the system prompt
/set <key> <value>Change a generation parameter
/show infoShow current model information
/show paramsShow current generation parameters
/exitExit the chat

Enter """ to start or finish multiline input. Press Ctrl+C during generation to interrupt the current response.

Deploy a Model (load)​

The load command loads a downloaded model into the LlamaPi service. The command finishes after loading completes, and closing the terminal does not affect the deployed model.

Load and deploy one model instance:

llamapi load qwen3:4b

Load multiple instances:

llamapi load qwen3:4b --instance 2

Set a runtime ID:

llamapi load qwen3:4b --id assistant

Third-party applications and API requests should use the actual runtime ID shown by llamapi ps.

List Deployed Models​

llamapi ps

This command displays each model's runtime ID, type, inference platform, state, instance count, and automatic-loading state.

Resize Instances​

Resize a deployed model to three instances:

llamapi load assistant --instance 3

More instances can increase parallel request capacity but consume more hardware resources. Select a count appropriate for the device.

Unload a Model​

llamapi unload assistant

Unloading ends the model deployment and releases its runtime resources, but it does not remove the local model files.

Use an Embedding Model​

Embedding models cannot be used for chat through llamapi run. Download and deploy the model first:

llamapi pull bge-m3
llamapi load bge-m3
llamapi ps

Then call /v1/embeddings. See the API Reference for request details.

A deployment created with load lasts only while the current LlamaPi service is running. To load a model automatically when the service starts, continue with Persistent Deployment.