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LatestXiaomi7B-Instruct
XiaomiAny-to-Any

Xiaomi's MiMo-Audio 7B Tackles Complex Speech Tasks

This new instruction-tuned model from Xiaomi can handle a flexible combination of audio and text inputs and outputs, from transcription to voice synthesis.

Sep 18, 2025
NotableMIT
MiMo-Audio-7B-Instruct

Xiaomi has released MiMo-Audio-7B-Instruct, a versatile 7-billion-parameter model designed to handle a wide array of speech and audio tasks. Published under a permissive MIT license, the model marks a notable open-source contribution from the major electronics company, providing a powerful new tool for developers working with audio AI.

The key innovation of MiMo-Audio is its "any-to-any" architecture. Unlike specialized models that perform a single function, MiMo-Audio is a generalist system that can process and generate audio and text in flexible combinations. This allows it to act as a unified solution for multiple distinct tasks.

A Unified Model for Speech AI

According to its release materials on Hugging Face, the instruction-tuned model is capable of performing a variety of functions, including:

  • Speech Recognition (ASR): Transcribing spoken audio to text.
  • Text-to-Speech (TTS): Synthesizing speech from written text.
  • Speech-to-Speech Translation (S2ST): Translating spoken language directly into another spoken language.
  • Audio Captioning and Generation: Describing sounds or creating audio from text prompts.

This flexibility makes MiMo-Audio a compelling foundation for building complex voice-enabled applications. By releasing a capable, general-purpose audio model under an open license, Xiaomi is providing a significant building block for the open-source AI community and a strong alternative to proprietary speech APIs.

Sources

  • XiaomiMiMo/MiMo-Audio-7B-Instruct

    Hugging Face

    Visit
OlderOpenBMB Releases VoxCPM for Open Voice SynthesisOpenBMB · Text → Speech · last yearNewerQwen3-Omni Arrives With Any-to-Any MultimodalityQwen · Alibaba · Any-to-Any · last year

Get the model

Hugging Face

Specs

Parameters7B
Context window8K tokens
Size16 GB
PrecisionBF16
ArchitectureMiMoAudioModel
LicenseMIT
Downloads1.6K
Likes172

Can you run it?

Runs on a laptop — about 7 GB at 4-bit.

  • BF16 (as published)

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    18.2 GB
  • 8-bit

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    10.7 GB
  • 4-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    7 GB
Your machine
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Any-to-AnyText → SpeechSpeech → Text

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