LLM Edge Studio

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LLM Edge Studio

LLM Edge Studio

Sure — here’s a shorter NXP Community post draft for LLM Edge Studio:


Running Local LLMs on i.MX with Ara240 DNPU using LLM Edge Studio

In this post, I want to share a quick walkthrough of LLM Edge Studio, an NXP launcher application designed to test supported Large Language Models running locally on i.MX platforms with Ara240 DNPU acceleration. [github.com]

LLM Edge Studio provides a simple GUI to select a model, load it, enter prompts, and interact with an LLM directly at the edge. It communicates with the Ara240 Runtime SDK through the eIQ AAF Connector, using a REST-based interface for prompt submission and streaming token responses. [github.com]

Supported Platforms

Key Features

  • Local LLM inference on supported i.MX platforms
  • Ara240 DNPU acceleration
  • GUI-based model selection and prompt input
  • Streaming token output
  • Integration with eIQ AAF Connector and Ara240 Runtime SDK
  • Support for prebuilt .deb package installation or building from source [github.com]

Supported Models

The current version supports the following Ara240-optimized models:

These models are provided as Ara240-compatible model.dvm files and are intended for local execution on the target platform. [github.com]

Basic Installation

After making sure the Ara240 Runtime SDK is installed on the target board, copy the Debian package to the board:

scp llm-edge-studio.deb root@<ip_addr>:

Install it with:

dpkg -i llm-edge-studio.deb

The installation may take a few minutes because the required models are downloaded during setup. [github.com]

Running LLM Edge Studio

Start the application with:

run_llm_edge_studio

Before launching, make sure the Ara240 runtime service is running:

systemctl status rt-sdk-ara2.service --no-pager -l

Once the GUI appears, click LOAD to load the selected model. After the model is ready, enter a prompt and submit it to start interacting with the LLM. [github.com]

Walkthrough Video

In the attached video, I show how to launch LLM Edge Studio, load a supported model, submit a prompt, and view the generated response running locally on the i.MX platform with Ara240 DNPU acceleration.

Video:

(マイビデオを表示)

Notes and Limitations

  • A single application instance can load only one model at a time.
  • Multiple models cannot currently be assigned to different endpoints within the same instance.
  • The UI is designed for 1920x1080 resolution; higher-resolution displays may show layout issues.
  • A proper 5V/3A power supply is recommended to avoid instability or board resets during inference. [github.com]

Summary

LLM Edge Studio is a useful tool for quickly evaluating local LLM inference on NXP i.MX platforms using Ara240 DNPU acceleration. It provides a simple workflow for model loading, prompt testing, and observing token streaming directly at the edge.

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