Xiaomi Open-Sources Breakthrough Audio AI Model

Xiaomi has fully open-sourced its MiDashengLM-7B multimodal large language model, marking a significant advancement in audio understanding technology. The model demonstrates 20x faster inference speeds compared to industry leaders while setting new performance benchmarks across 22 public evaluation sets.

Technical Architecture

The model employs an innovative dual-core design:

• Xiaomi Dasheng audio encoder
• Qwen2.5-Omni-7B Thinker autoregressive decoder

This architecture enables unified processing of speech, ambient sounds, and music - a rare capability in current audio AI systems. Traditional models typically specialize in one sound type, but MiDashengLM-7B maintains high accuracy across all categories.

Performance Milestones

Key achievements include:

• First Token delay reduced to 25% of leading competitors
• Data throughput efficiency increased 20x under same GPU memory conditions
• New records set on 22 multimodal evaluation benchmarks

The efficiency gains come from optimized architecture and training strategies that reduce computational costs without sacrificing accuracy.

Dasheng Series Evolution

MiDashengLM-7B represents a major upgrade in Xiaomi's audio AI technology:

• Builds on multiple generations of Dasheng encoder development
• Creates complete technical chain from encoding to multimodal understanding
• Enables future applications across Xiaomi's IoT ecosystem

Future Development Roadmap

Xiaomi plans to:

1. Enable offline deployment on terminal devices
2. Enhance privacy protection and reduce cloud dependency
3. Develop natural language sound editing capabilities
4. Expand integration with smart devices ecosystem

The move toward terminal deployment could revolutionize accessibility of high-quality audio AI services.

Open Source Impact

The full open-sourcing of MiDashengLM-7B:

• Lowers barriers for researchers and startups
• Accelerates industry-wide audio AI development
• Promotes collaborative innovation
• Supports broader adoption of multimodal technologies

Key Points:

• 20x faster inference than current leading models
• Unified processing of speech, music and environmental sounds
• New records on 22 evaluation benchmarks
• Planned offline terminal deployment
• Fully open-source to drive industry innovation