Module-LLM

SKU:M140

Description

Module LLM is an integrated offline Large Language Model (LLM) inference module designed for terminal devices that require efficient and intelligent interaction. Whether for smart homes, voice assistants, or industrial control, Module LLM provides a smooth and natural AI experience without relying on the cloud, ensuring privacy and stability. Integrated with the StackFlow framework and Arduino/UiFlow libraries, smart features can be easily implemented with just a few lines of code.
Powered by the advanced AX630C SoC processor, it integrates a 3.2 TOPs high-efficiency NPU with native support for Transformer models, handling complex AI tasks with ease. Equipped with 4GB LPDDR4 memory (1GB available for user applications, 3GB dedicated to hardware acceleration) and 32GB eMMC storage, it supports parallel loading and sequential inference of multiple models, ensuring smooth multitasking. The main chip's runtime power consumption of approximately 1.5W, making it highly efficient and suitable for long-term operation.
It features a built-in microphone, speaker, TF storage card, USB OTG, and RGB status light, meeting diverse application needs with support for voice interaction and data transfer. The module offers flexible expansion: the onboard SD card slot supports cold/hot firmware upgrades, and the UART communication interface simplifies connection and debugging, ensuring continuous optimization and expansion of module functionality. The USB port supports master-slave auto-switching, serving as both a debugging port and allowing connection to additional USB devices like cameras. Users can purchase the LLM debugging kit to add a 100 Mbps Ethernet port and kernel serial port, using it as an SBC.
The module is compatible with multiple models and comes pre-installed with the Qwen2.5-0.5B language model. It features KWS (wake word), ASR (speech recognition), LLM (large language model), and TTS (text-to-speech) functionalities, with support for standalone calls or pipeline automatic transfer for convenient development. Future support includes Qwen2.5-1.5B, Llama3.2-1B, and InternVL2-1B models, allowing hot model updates to keep up with community trends and accommodate various complex AI tasks. Vision recognition capabilities include support for CLIP, YoloWorld, and future updates for DepthAnything, SegmentAnything, and other advanced models to enhance intelligent recognition and analysis.
Plug and play with M5 hosts, Module LLM offers an easy-to-use AI interaction experience. Users can quickly integrate it into existing smart devices without complex settings, enabling smart functionality and improving device intelligence. This product is suitable for offline voice assistants, text-to-speech conversion, smart home control, interactive robots, and more.

Arduino IDE

This tutorial introduces how to program and control the Module LLM device using the Arduino IDE

UIFlow2.0

This tutorial introduces how to control the Module LLM device using the UIFlow2.0 graphical programming platform

Product Features

Offline inference, 3.2T@INT8 precision computing power
Integrated KWS (wake word), ASR (speech recognition), LLM (large language model), TTS (text-to-speech generation)
Multi-model parallel processing
Onboard 32GB eMMC storage and 4GB LPDDR4 memory
Onboard microphone and speaker
Serial communication
SD card firmware upgrade
Supports ADB debugging
RGB indicator light
Built-in Ubuntu system
Supports OTG functionality
Compatible with Arduino/UIFlow

Includes

1x Module LLM
1x Ethernet Debug Board

Applications

Offline voice assistants
Text-to-speech conversion
Smart home control
Interactive robots

Specifications

Specification	Parameter
Processor SoC	AX630C@Dual Cortex A53 1.2 GHz MAX.12.8 TOPS @INT4 and 3.2 TOPS @INT8
Memory	4GB LPDDR4 (1GB system memory + 3GB dedicated for hardware acceleration)
Storage	32GB eMMC5.1
Communication	Serial communication default baud rate 115200@8N1 (adjustable)
Microphone	MSM421A
Audio Driver	AW8737
Speaker	8Ω@1W, Size:2014 cavity speaker
Built-in Units	KWS (wake word), ASR (speech recognition), LLM (large language model), TTS (text-to-speech)
RGB Light	3x RGB LED@2020 driven by LP5562 (status indication)
Power	Idle: 5V@0.5W, Full load: 5V@1.5W
Button	For entering download mode for firmware upgrade
Upgrade Port	SD card / Type-C port
Working Temp	0-40°C
Product Size	545413mm
Packaging Size	1339516mm
Product Weight	17.4g
Packaging Weight	32.0g

AX630C

PinMap

Module LLM	RXD	TXD
Core (Basic)	G16	G17
Core2	G13	G14
CoreS3	G18	G17

LLM Module Pin Switching

LLM Module has reserved soldering pads for pin switching. In cases of pin multiplexing conflicts, the PCB trace can be cut and reconnected to other sets of pins.

Using CoreS3 as an example, the first column (left green box) represents the TX pin for serial communication. Users can choose one from four options based on their needs (from top to bottom: pins G18, G7, G14, G10), with IO18 as the default pin. To switch to another pin, cut the connection line at the red solder pad (recommended to use a blade for cutting). Then, connect any one of the three remaining pins. The second column (right green box) is for RX pin switching. The operation is the same as above, where users also choose one from four options.

Schematic

Module LLM Schematic Download

Module Size

Indicator Light

LLM Module working status indicator:
- Red: Device is initializing
- Green: Device initialized successfully
LLM Module upgrade status indicator:
- Blue flashing: Application package updating
- Red:Application package update failed
- Green: Application package updated successfully

Note on Model Replacement

The LLM Module supports models in a proprietary format requiring special processing to function properly. Therefore, existing models on the market cannot be used directly.

UIFlow

Arduino

Firmware Update

Development Framework

Coming soon...

Development Resources

Video

Module LLM product introduction and example showcase

AI Benchmark Comparison