XiaomiMiMo/MiMo-Audio

Health v2 · maintenance only

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1077 stars · 107 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Xiaomi's open-source 7B audio language model family (Base and Instruct) plus a 1.2B RVQ audio tokenizer, pretrained on 100M+ hours of audio to enable few-shot generalization across audio tasks. It jointly models text and audio tokens for understanding, speech generation, TTS, voice conversion, and speech editing.

Use cases

• build an audio understanding model that answers questions about speech and sound
• text-to-speech and instruct-TTS with natural voices
• speech continuation for generating talk shows or recitations
• voice conversion and style transfer with few examples
• speech-to-text transcription and audio reasoning benchmarks
• few-shot audio task generalization without task-specific fine-tuning

When to choose

• you need a single open-source model covering both audio understanding and generation
• you want SOTA open-source performance on audio benchmarks like MMAU or MMSU
• you need few-shot generalization to audio tasks without fine-tuning
• you want an Apache-2.0 licensed audio LLM with released checkpoints and eval suite

When to avoid

• you need lightweight on-device audio processing rather than a 7B GPU model
• you only need simple ASR where Whisper-class models suffice
• you lack GPU resources for large model inference
• you need production hardening rather than a research codebase

Facets

library · maturity active

machine-learning audio-processing speech-recognition tts llm-inference artificial-intelligence speech-processing large-language-models python audio-language-model few-shot-learning audio-tokenizer rvq speech-generation instruction-tuning 7b-model multimodal audio natural-language-processing gpu linux

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