alt.freeweights.mimo / MiMo-V2.5-ASR
From: XiaomiMiMo <huggingface.co/XiaomiMiMo>Newsgroups: alt.freeweights.mimoSubject:

MiMo-V2.5-ASR

Date: 2026-11-15Commit: 227ce4cSigned: 2DC28CC7B26A283B ✓

Automatic speech recognition model with 7.6B parameters. Safetensors weights, 32.1 GB in all. Published by XiaomiMiMo under MIT.

7.6B params32.1GBMiMo-V2.5-ASRsafetensorspermissive
FactsParams7.6BSize32.1 GBFormatssafetensorsTaskautomatic speech recognitionLicenseMITFrom sourcepermissive
$ fw get XiaomiMiMo/MiMo-V2.5-ASR
# manifest sha256 f44e6d0a51af… · 32.1 GB · 22 files
$ fw verify ./MiMo-V2.5-ASR XiaomiMiMo/MiMo-V2.5-ASR
From sourceHosted (signed)XiaomiMiMo/MiMo-V2.5-ASRLast check: 2026-11-15 02:50 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Works with

Overview

Size
32.1 GB
Weights
32.1 GB (safetensors)
Parameters
7.6B
Formats
safetensors
Task
automatic speech recognition
License
MIT (permissive)
Files
22, each with a sha256
Publisher
XiaomiMiMo
Added
2026-11-15
Section
alt.freeweights.mimo
Lineage

Original release from the publisher.

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Publisher at the pinned commit→You

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BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 02:50 UTCpassed

Model card

From the publisher at commit 227ce4c. Shown as plain text with links; images open at the publisher.

Image: Xiaomi-MiMo

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MiMo-V2.5-ASR: Robust Speech Recognition Across

Languages, Dialects, and Complex Acoustic Scenarios

━━━━━━━━━━━━━━━━━━━━━━━━━━━

| 💻 GitHub &nbsp;| 🚀 Online Demo &nbsp;| 📰 Blog &nbsp;|

Introduction#

MiMo-V2.5-ASR is a state-of-the-art end-to-end automatic speech recognition (ASR) model developed by the Xiaomi MiMo team. It is built to deliver accurate and robust transcription across Mandarin Chinese and English, multiple Chinese dialects, code-switched speech, song lyrics, knowledge-intensive content, noisy acoustic environments, and multi-speaker conversations. MiMo-V2.5-ASR achieves state-of-the-art results on a wide range of public benchmarks.

Abstract#

Automatic speech recognition systems are expected to faithfully transcribe speech signals that originate from diverse languages, dialects, accents, and domains, and that are captured under a wide variety of acoustic conditions. While conventional end-to-end models perform well on in-domain data, they still fall short of real-world requirements in challenging scenarios such as dialect mixing, code-switching, knowledge-intensive content, noisy environments, and multi-speaker conversations. We present MiMo-V2.5-ASR, a large-scale end-to-end speech recognition model developed by the Xiaomi MiMo team. Through large-scale mid-training, high-quality supervised fine-tuning, and a novel reinforcement-learning algorithm, MiMo-V2.5-ASR achieves systematic improvements along the following dimensions:

  • 🗣️ Chinese Dialects: Native support for Wu, Cantonese, Hokkien, Sichuanese, and more.
  • 🔀 Code-Switch: Seamless Chinese–English code-switching transcription with no language tags required.
  • 🎵 Song Recognition: High-precision lyrics transcription for Chinese and English songs, even with mixed accompaniment and vocals.
  • 🔊 Noisy Environments: Robust recognition under heavy noise, far-field capture, and other adverse acoustic conditions.
  • 👥 Multi-Speaker: Accurate transcription of overlapping, multi-party conversations such as meetings.
  • 🇬🇧 Complex English Scenarios: Leading performance on the Open ASR Leaderboard for challenging English benchmarks such as AMI.
  • 📚 Knowledge-Intensive Recognition: Precise recognition of classical poetry, technical terminology, personal names, place names, and other knowledge-dense material.
  • 📝 Native Punctuation: Punctuation generated natively from prosody and semantics, delivering ready-to-use transcripts with no post-processing needed.

Results#

MiMo-V2.5-ASR has been evaluated across a broad set of benchmarks spanning standard Mandarin and English, Chinese dialects, lyric recognition, and internal business scenarios. The chart below summarizes the average performance of MiMo-V2.5-ASR across these scenarios.

Image: ASR Results

For per-benchmark numbers and specific qualitative cases, please refer to our blog.

Model Download#

Models🤗 Hugging Face🤖️ ModelScope
MiMo-Audio-TokenizerXiaomiMiMo/MiMo-Audio-TokenizerXiaomiMiMo/MiMo-Audio-Tokenizer
MiMo-V2.5-ASRXiaomiMiMo/MiMo-V2.5-ASRXiaomiMiMo/MiMo-V2.5-ASR
pip install huggingface-hub

hf download XiaomiMiMo/MiMo-Audio-Tokenizer --local-dir ./models/MiMo-Audio-Tokenizer
hf download XiaomiMiMo/MiMo-V2.5-ASR --local-dir ./models/MiMo-V2.5-ASR

Getting Started#

Spin up the MiMo-V2.5-ASR demo in minutes with the built-in Gradio app.

Prerequisites (Linux)#
  • Python 3.12
  • CUDA >= 12.0
Installation#
git clone https://github.com/XiaomiMiMo/MiMo-V2.5-ASR.git
cd MiMo-V2.5-ASR
pip install -r requirements.txt
pip install flash-attn==2.7.4.post1

\[!Note] If the compilation of flash-attn takes too long, you can download the precompiled wheel and install it manually:

pip install /path/to/flash_attn-2.7.4.post1+cu12torch2.6cxx11abiFALSE-cp312-cp312-linux_x86_64.whl
Run the Demo#
python run_mimo_asr.py

This launches a local Gradio interface for MiMo-V2.5-ASR. You can:

  • Upload an audio file or record directly from your microphone.
  • Optionally specify a language tag (Chinese / English / Auto) to bias the model for a specific language, or leave it to Auto for automatic language detection (recommended for code-switched speech).
  • The demo calls the asr_sft() interface under the hood.

The interface provides a Model Configuration tab for setting local model and tokenizer paths, and a Speech Recognition tab where you drop in audio, pick a language tag, and hit Transcribe — the decoded text and processing status stream into the panels on the right.

Image: MiMo-V2.5-ASR Gradio Demo

Figure: Gradio demo for MiMo-V2.5-ASR — upload an audio clip or record from your microphone, choose a language tag, and get the transcription on the right.

To load the model and tokenizer automatically at startup, pass their paths on the command line:

python run_mimo_asr.py \
    --model-path ./models/MiMo-V2.5-ASR \
    --tokenizer-path ./models/MiMo-Audio-Tokenizer

Otherwise, enter the local paths for MiMo-Audio-Tokenizer and MiMo-V2.5-ASR in the Model Configuration tab, then start transcribing!

Python API#

Basic usage with the asr_sft interface:

from src.mimo_audio.mimo_audio import MimoAudio

model = MimoAudio(
    model_path="./models/MiMo-V2.5-ASR",
    tokenizer_path="./models/MiMo-Audio-Tokenizer",
)

# Automatic language detection (recommended for code-switching)
text = model.asr_sft("path/to/audio.wav")
print(text)

# With explicit language tag
text_zh = model.asr_sft("path/to/audio.wav", audio_tag="<chinese>")
text_en = model.asr_sft("path/to/audio.wav", audio_tag="<english>")

Citation#

@misc{coreteam2026mimov25asr,
      title={MiMo-V2.5-ASR: Robust Speech Recognition Across Languages, Dialects, and Complex Acoustic Scenarios},
      author={LLM-Core-Team Xiaomi},
      year={2026},
      url={https://github.com/XiaomiMiMo/MiMo-V2.5-ASR},
}

Contact#

Please contact us at mimo@xiaomi.com or open an issue if you have any questions.

Use Restrictions#

You are solely responsible for your use of XiaomiMiMo/MiMo-V2.5-ASR and any outputs, actions, or consequences arising therefrom, and you agree not to use the XiaomiMiMo/MiMo-V2.5-ASR or any derivatives thereof:

  • For any unlawful, fraudulent, or malicious purpose, or in any manner that violates any applicable laws or regulations;
  • To infringe upon the intellectual property rights, privacy rights, publicity rights, or other lawful rights or interests of any third party;
  • To exploit, harm, harass, defame, unlawfully discriminate against, or otherwise adversely affect any individual or group, including minors or vulnerable persons;
  • For any military purpose or application;
  • To engage in or facilitate malicious cyber activities, including but not limited to malware, ransomware, phishing, credential theft, or unauthorized access, or any activity intended to compromise or unlawfully control computer systems, networks, or encryption systems;
  • To access, collect, process, disclose, or disseminate personal data or other protected information without appropriate authorization or lawful basis; or to access, interact with, scrape, or automate any third-party platform or service in violation of any applicable laws, policies, or authorization requirements;
  • To use the XiaomiMiMo/MiMo-V2.5-ASR in a manner that autonomously executes high-risk actions without appropriate human oversight or authorization.

This notice is an informational reminder only and does not amend the applicable model licence or impose additional licence conditions. The permissions granted under that licence remain unaffected. Nothing in this notice restricts uses permitted by applicable law, including applicable exceptions and limitations.

Usage enquiries and complaints#

mimo-legal@xiaomi.com. For information on submitting a complaint, please visit the https://mimo.xiaomi.com.

Files

22 files · 32.1 GBWeights 32.1 GB (safetensors). Sizes and sha256 from the signed manifest.
Show all 22 files with their sha256
FileSizesha256
.gitattributes1.75 KBaa0a800ed0db670804b3e88bf0511b57228bffa1490de17bb39c8dbf8ffc3e4d
README.md9.95 KB8eeab5ba126dcfaf3a7c031bf400b95c6e8d03b6de88012c077193356aa44786
added_tokens.json788 B45a03de178f22795c611428bf0798d9acaa9792bb8484870b7e8dab8ad34e0c3
assets/MiMo_ASR_Demo.png73.2 KBd4e1433c408a52a626214463ebd449b403128072064615b82cc207cf03f813e8
assets/MiMo_ASR_Results.png449 KB2c3f5148a5040f323e96158703ad44f6854bff72bbad7a656b8a526a6404972c
assets/XiaomiMIMO.png290 KB89cf9afd532aa29697d65880b1f0dcb4f3286289eb3e8d697c46f32545cf1444
chat_template.jinja8.47 KBe63cd39d862e28059a94632cba03160eeb15c771bf7e0abd76f29db4eaa0b793
config.json2.79 KB1bfaf8285e1e1f5e78035d223457749424950efa847f1cd02aa8828c1771bfeb
generation_config.json77 B575fff5a84761eea35265538cff4609365ca06355b064a44f16d7ab457ef73da
merges.txt1.67 MB8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5
model-00001-of-00007.safetensors4.96 GB8e424db00a4258cf62b626d4bab42627d619d537d9ae975bae54591b1bbb25ae
model-00002-of-00007.safetensors4.96 GBd83ee8aab141033fdb77a4d52d1bcd839247007198159f71f6b61db809e9987e
model-00003-of-00007.safetensors4.96 GB409d6d66d78ab50bddfa02af7108a1486c8018fb00231f62a4ea14c594a57a24
model-00004-of-00007.safetensors4.96 GBd8bb46073f13a61b39249787668f69222ab5e76fecd1240604ecff1e5b0251b9
model-00005-of-00007.safetensors4.96 GBd8aa4249ee58a1762187a589f2fb0053cc9d2833ef3beb5cefc75075d227dfca
model-00006-of-00007.safetensors3.20 GBcecc940b16d122e807859cf919deceb2d3a9ac1668b27b876252e20293117b0c
model-00007-of-00007.safetensors4.07 GBbf197fef74fa019c2567e6b4d054a0335fd15234ddd7c9b891a303a7102e031b
model.safetensors.index.json62.3 KB6e890bcef1b854b9b4da575f4c7490770fcb5aa1740fd3421877b5517eef2684
special_tokens_map.json616 B6676f091c8bc4d1b50146427cfde92073402866b87b6e39223227931b70083e9
tokenizer.json11.4 MBd91a78cce6441fd6855038f6764fc5f811ae949d9b89f43ac326cddfe91c66db
tokenizer_config.json6.09 KBfcd8ec17c91cd380f6c2e78bc409463949a546db1fd4182ee50856895f20115d
vocab.json2.78 MBca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
227ce4c5e6 pinned now2026-11-15 02:50 UTC22 files · 32.1 GB

Use it

$ fw get XiaomiMiMo/MiMo-V2.5-ASR
# manifest sha256 f44e6d0a51af… · 32.1 GB · 22 files
$ fw verify ./MiMo-V2.5-ASR XiaomiMiMo/MiMo-V2.5-ASR
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/XiaomiMiMo/MiMo-V2.5-ASR.json --dir ./MiMo-V2.5-ASR $ python3 fw.py verify ./MiMo-V2.5-ASR ./XiaomiMiMo__MiMo-V2.5-ASR.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download XiaomiMiMo/MiMo-V2.5-ASR --revision 227ce4c5e64e356007ad948781f0e8b55a1beba0 --local-dir ./MiMo-V2.5-ASR
transformersSpeech recognition with the transformers pipeline.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from transformers import pipeline asr = pipeline("automatic-speech-recognition", model="XiaomiMiMo/MiMo-V2.5-ASR", revision="227ce4c5e64e356007ad948781f0e8b55a1beba0") print(asr("audio.wav")["text"])

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
8eeab5ba126dcfaf3a7c031bf400b95c6e8d03b6de88012c077193356aa44786
Terms gate
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Read the license text

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Provenance

From: XiaomiMiMo <huggingface.co/XiaomiMiMo>Newsgroups: alt.freeweights.mimoSubject: MiMo-V2.5-ASRDate: 2026-11-15Commit: 227ce4cSigned: 2DC28CC7B26A283B ✓
Upstream
XiaomiMiMo/MiMo-V2.5-ASR
Pinned commit
227ce4c5e64e356007ad948781f0e8b55a1beba0
Manifest
MiMo-V2.5-ASR.json · .minisig
Manifest sha256
f44e6d0a51afd6a810bef68abcbf2ddf0059d7ba30a36a7493e08a0b3cc30df4
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 02:50 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/XiaomiMiMo/MiMo-V2.5-ASR.json $ curl -O https://freeweights.allternit.com/manifests/XiaomiMiMo/MiMo-V2.5-ASR.json.minisig $ minisign -Vm MiMo-V2.5-ASR.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

1 model in the catalog name this one as their parent.

Quantizations
1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download XiaomiMiMo/MiMo-V2.5-ASR
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. MiMo-V2.5-ASR.json. Provenance. Takedown history: none.

Variants

1 quantized or adapter build of MiMo-V2.5-ASR. Each has its own license check and page.

From: XiaomiMiMo <huggingface.co/XiaomiMiMo>Subject: MiMo-7B-Base
From: XiaomiMiMo <huggingface.co/XiaomiMiMo>Subject: MiMo-V2-Flash
From: unsloth <huggingface.co/unsloth>Subject: MiMo-V2-Flash-GGUF
From: XiaomiMiMo <huggingface.co/XiaomiMiMo>Subject: MiMo-V2.5
From: mlx-community <huggingface.co/mlx-community>Subject: MiMo-V2.5-ASR-MLX-8bit
From: bartowski <huggingface.co/bartowski>Subject: MiMo-V2.5-GGUF