LFM2.5-Audio-1.5B-JP
This repository contains GGUF quantizations of LiquidAI/LFM2.5-Audio-1.5B-JP for use with llama.cpp.
Available files
| File | Quantization | Size |
|---|---|---|
LFM2.5-Audio-1.5B-JP-F32.gguf |
F32 (language model) | 4.4 GB |
LFM2.5-Audio-1.5B-JP-F16.gguf |
F16 (language model) | 2.2 GB |
LFM2.5-Audio-1.5B-JP-Q8_0.gguf |
Q8_0 (language model) | 1.2 GB |
LFM2.5-Audio-1.5B-JP-Q4_0.gguf |
Q4_0 (language model) | 664 MB |
mmproj-LFM2.5-Audio-1.5B-JP-F32.gguf |
F32 (audio encoder / multimodal projector) | 695 MB |
mmproj-LFM2.5-Audio-1.5B-JP-F16.gguf |
F16 (audio encoder / multimodal projector) | 413 MB |
mmproj-LFM2.5-Audio-1.5B-JP-Q8_0.gguf |
Q8_0 (audio encoder / multimodal projector) | 280 MB |
mmproj-LFM2.5-Audio-1.5B-JP-Q4_0.gguf |
Q4_0 (audio encoder / multimodal projector) | 210 MB |
vocoder-LFM2.5-Audio-1.5B-JP-F32.gguf |
F32 (vocoder / audio detokenizer) | 739 MB |
vocoder-LFM2.5-Audio-1.5B-JP-F16.gguf |
F16 (vocoder / audio detokenizer) | 370 MB |
vocoder-LFM2.5-Audio-1.5B-JP-Q8_0.gguf |
Q8_0 (vocoder / audio detokenizer) | 197 MB |
vocoder-LFM2.5-Audio-1.5B-JP-Q4_0.gguf |
Q4_0 (vocoder / audio detokenizer) | 104 MB |
tokenizer-LFM2.5-Audio-1.5B-JP-F32.gguf |
F32 (audio tokenizer) | 268 MB |
tokenizer-LFM2.5-Audio-1.5B-JP-F16.gguf |
F16 (audio tokenizer) | 134 MB |
tokenizer-LFM2.5-Audio-1.5B-JP-Q8_0.gguf |
Q8_0 (audio tokenizer) | 72 MB |
tokenizer-LFM2.5-Audio-1.5B-JP-Q4_0.gguf |
Q4_0 (audio tokenizer) | 46 MB |
Runners
runners folder contains pre-built binaries for various architectures:
llama-liquid-audio-clillama-liquid-audio-server
🏃 How to run LFM2.5-Audio-JP
CLI
Set env variables.
export CKPT=/path/to/LFM2.5-Audio-1.5B-JP-GGUF
export INPUT_WAV=/path/to/input.wav
export OUTPUT_WAV=/path/to/output.wav
ASR (audio -> text)
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform ASR in japanese." --audio $INPUT_WAV
TTS (text -> audio)
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Perform TTS in japanese." -p "こんにちは、お元気ですか?" --output $OUTPUT_WAV
Interleaved (audio/text -> audio + text)
./llama-liquid-audio-cli -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf -sys "Respond with interleaved text and audio." --audio $INPUT_WAV --output $OUTPUT_WAV
Server
Start server
export CKPT=/path/to/LFM2.5-Audio-1.5B-JP-GGUF
./llama-liquid-audio-server -m $CKPT/LFM2.5-Audio-1.5B-Q4_0.gguf -mm $CKPT/mmproj-LFM2.5-Audio-1.5B-Q4_0.gguf -mv $CKPT/vocoder-LFM2.5-Audio-1.5B-Q4_0.gguf --tts-speaker-file $CKPT/tokenizer-LFM2.5-Audio-1.5B-Q4_0.gguf
Use liquid_audio_chat.py script to communicate with the server.
uv run liquid_audio_chat.py
Source Code for Runners
Runners are built from https://github.com/ggml-org/llama.cpp/pull/18641.
📬 Contact
- Got questions or want to connect? Join our Discord community
- If you are interested in custom solutions with edge deployment, please contact our sales team.
License
The code in this repository and associated weights are licensed under the LFM Open License v1.0.
The code for the audio encoder is based on Nvidia NeMo, licensed under Apache 2.0, and the canary-180m-flash checkpoint, licensed under CC-BY 4.0. To simplify dependency resolution, we also ship the Python code of Kyutai Mimi, licensed under the MIT License. We also redistribute weights for Kyutai Mimi, licensed under CC-BY-4.0.
Citation
@article{liquidai2025lfm2,
title={LFM2 Technical Report},
author={Liquid AI},
journal={arXiv preprint arXiv:2511.23404},
year={2025}
}