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Liquid AI releases LFM3-Omni-2B multimodal model with voice output

By PulseAugur Editorial · [1 sources] ·

Liquid AI has released LFM3-Omni-2B, a new 2B parameter model capable of processing text, images, video, and audio, and responding with text or 24 kHz speech. While Ollama and LM Studio can load the model, only llama.cpp currently enables its voice output capabilities. The model, built on LFM3-1.7B-Base, integrates various encoders for multimodal input and a Liquid Audio Codec for speech output, featuring a 32K token context window. Comparisons suggest LFM3-Omni-2B excels in voice tasks but is outperformed by specialized models like LFM3-VL-2B for vision-centric tasks and by larger models like Gemma 4 for voice assistant functionalities. AI

IMPACT Enables local execution of multimodal AI with voice output, offering a new option for developers and users interested in on-device AI capabilities.

RANK_REASON The item describes how to run a specific open-source multimodal LLM locally using llama.cpp, focusing on technical implementation details and comparisons with other tools.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Liquid AI releases LFM3-Omni-2B multimodal model with voice output

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The item describes how to run a specific open-source multimodal LLM locally using llama.cpp, focusing on technical implementation details and comparisons with other tools.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Alan West ·

    How to Run LFM3-Omni-2B GGUF Locally (Only llama.cpp Makes It Talk Back)

    <p>LFM3-Omni-2B is Liquid AI's new 2B model that takes text, images, video and audio in and answers in text or 24 kHz speech. The Q4_K_M GGUF is 1.1 GB, plus a 292 MB mmproj file, and llama.cpp v0.8.0 runs all of it, voice output included. Ollama and LM Studio load it too, but ne…

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