Model reference · open weights

Fun-ASR-MLT-Nano-2512

Audio FunAudioLLM Speech→text 1 build Open weights 825 dl/mo

Fun-ASR-MLT-Nano-2512 is an open-weight audio or speech model from FunAudioLLM. Fun-ASR-MLT-Nano-2512 (BF16) weighs 2.0 GB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • Fun-ASR-MLT-Nano-2512 is an 800M-parameter automatic speech recognition model developed by FunAudioLLM.
  • It supports 31 languages with a focus on East and Southeast Asian languages and is trained on hundreds of thousands of hours of multilingual speech.
  • The model is released under the Apache 2.0 license.

Summary of the FunAudioLLM/Fun-ASR-MLT-Nano-2512 model card, 2026-10-01

What it is

Released byFunAudioLLM
Released2025-12-15
VRAM2.0 GB for the weights

What it runs on

Memory and cards for Fun-ASR-MLT-Nano-2512 (BF16)

2.0 GBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What FunAudioLLM says about Fun-ASR-MLT-Nano-2512

Read the model card

⭐ Powered by FunASR — please give us a GitHub Star!

This model is part of the FunASR ecosystem — one industrial-grade open-source toolkit for ASR · VAD · punctuation · speaker diarization · emotion / event · LLM-ASR. A Star really helps the project (and keeps you updated):

🌟 FunASR · 🌟 SenseVoice · 🌟 Fun-ASR · 🌟 FunClip

Fun-ASR-MLT-Nano-2512

「简体中文」|「English」

Fun-ASR-MLT-Nano-2512 is the 800M-parameter multilingual checkpoint in the Fun-ASR family. It is trained on hundreds of thousands of hours of multilingual speech and supports 31 languages, with emphasis on East and Southeast Asian languages. For the Chinese, English, and Japanese checkpoint trained on tens of millions of hours, use Fun-ASR-Nano-2512.

| Core Features | Performance Evaluation | Environment Setup | Usage Tutorial

Model Repository: modelscope, huggingface

Model NameTask DetailsTraining DataParameters
Fun-ASR-Nano (⭐ 🤗)Speech recognition supports Chinese, English, and Japanese. Chinese includes support for 7 dialects (Wu, Cantonese, Min, Hakka, Gan, Xiang, Jin) and 26 regional accents (Henan, Shanxi, Hubei, Sichuan, Chongqing, Yunnan, Guizhou, Guangdong, Guangxi and more than 20 other regions). English and Japanese cover multiple regional accents. Additional features include lyric recognition and rap speech recognition.Tens of millions of hours800M
Fun-ASR-MLT-Nano (⭐ 🤗)Speech recognition supports Chinese, English, Cantonese, Japanese, Korean, Vietnamese, Indonesian, Thai, Malay, Filipino, Arabic, Hindi, Bulgarian, Croatian, Czech, Danish, Dutch, Estonian, Finnish, Greek, Hungarian, Irish, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovak, Slovenian, Swedish, and 31 languages in total.Hundreds of thousands of hours800M

What's New 🔥

  • 2025/12: Fun-ASR-MLT-Nano-2512 is the multilingual 800M checkpoint, trained on hundreds of thousands of hours of speech and covering 31 languages.
  • 2024/7: FunASR is a fundamental speech recognition toolkit that offers a variety of features, including speech recognition (ASR), Voice Activity Detection (VAD), Punctuation Restoration, Language Models, Speaker Verification, Speaker Diarization and multi-talker ASR.

Core Features 🎯

This repository hosts the MLT checkpoint. Its supported-language scope differs from the standard Fun-ASR-Nano checkpoint.

  • 31 languages: Covers the languages listed in the model table above, with focused optimization on East and Southeast Asian languages.
  • Compact multilingual model: Uses approximately 800M parameters.
  • Language control: Accepts the language names shown in the inference example and supports multilingual recognition.
  • Context controls: The FunASR inference API exposes hotwords and inverse text normalization (ITN).

Environment Setup 🐍

python -m pip install -U "funasr>=1.4.1"

# Optional: clone the example repo if you want to run the local demo scripts.
git clone https://github.com/FunAudioLLM/Fun-ASR.git
cd Fun-ASR
python -m pip install -r requirements.txt

TODO

  • [ ] Support returning timestamps
  • [ ] Support speaker diarization
  • [ ] Support model training

Usage 🛠️

Inference

Using funasr for inference

from funasr import AutoModel

def main():
    model_dir = "FunAudioLLM/Fun-ASR-MLT-Nano-2512"
    model = AutoModel(
        model=model_dir,
        hub="hf",
        trust_remote_code=True,
        remote_code="./model.py",
        device="cuda:0",
    )

    wav_path = f"{model.model_path}/example/zh.mp3"
    res = model.generate(
        input=[wav_path],
        cache={},
        batch_size=1,
        hotwords=["开放时间"],
        # 中文、英文、粤语、日文、韩文、越南语、印尼语、泰语、马来语、菲律宾语、阿拉伯语、
        # 印地语、保加利亚语、克罗地亚语、捷克语、丹麦语、荷兰语、爱沙尼亚语、芬兰语、希腊语、
        # 匈牙利语、爱尔兰语、拉脱维亚语、立陶宛语、马耳他语、波兰语、葡萄牙语、罗马尼亚语、
        # 斯洛伐克语、斯洛文尼亚语、瑞典语 for Fun-ASR-MLT-Nano-2512
        language="中文",
        itn=True,

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

How it works

How audio & music work

Audio or textinputAudio modelrecognise / synthesiseText or audiooutputSpeech-to-text turns audio into text; text-to-speech and music models turn text into audio.
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