LFG-3 is an audio-language model that fuses the best-in-class conversational intelligence of Gemma 4 31B with a Parakeet audio encoder through a trained projection layer. Speech goes in, text comes out.

The model is the third iteration in a personal learning journey to answer the question: "Can I stand on the shoulders of giants and use limited compute resources to build a standout model that can understand what and how you say things, not just speech to text?"

The answer is Yes. LFG-3 was trained entirely on a single H100 from my house on nights and weekends. It ranks #1 on Voice Bench at the time of this release.

LFG-3 serves as an open exploration of just how adaptable the Gemma architecture can be for independent developers building multimodal applications.

Voice Bench Results

Usage

import soundfile as sf
from transformers import AutoModelForMultimodalLM, AutoProcessor

MODEL = "glenn2/LFG-3"
processor = AutoProcessor.from_pretrained(MODEL, trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained(
    MODEL, trust_remote_code=True, dtype="bfloat16", device_map="cuda"
)
audio, sr = sf.read("question.wav")  # 16 kHz mono


messages = [
    {"role": "system", "content": [{"type": "text", "text": "You are a helpful voice assistant. The user is speaking to you, and your reply will be read aloud."}]},
    {"role": "user", "content": [{"type": "audio", "audio": audio}]}, # Audio should be 16 kHz mono. 
]
# Process input
inputs = processor.apply_chat_template(
    messages,
    tokenize=True,
    return_dict=True,
    return_tensors="pt",
    add_generation_prompt=True,
    enable_thinking=True
).to(model.device)
input_len = inputs["input_ids"].shape[-1]

# Generate output
outputs = model.generate(**inputs, max_new_tokens=4096)
response = processor.decode(outputs[0][input_len:], skip_special_tokens=False)

# Parse output
print(processor.parse_response(response)["content"])  

Intended use

• Designed for English spoken questions/instructions → text answers.
• Inherits knowledge from the Gemma 4 31B IT model.