Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large
  Audio Language Models
We present Audio Flamingo 3 (AF3), a fully open state-of-the-art (SOTA) large
audio-language model that advances reasoning and understanding across speech,
sound, and music. AF3 introduces: (i) AF-Whisper, a unified audio encoder
trained using a novel strategy for joint representation learning across all 3
modalities of speech, sound, and music; (ii) flexible, on-demand thinking,
allowing the model to do chain-of-thought-type reasoning before answering;
(iii) multi-turn, multi-audio chat; (iv) long audio understanding and reasoning
(including speech) up to 10 minutes; and (v) voice-to-voice interaction. To
enable these capabilities, we propose several large-scale training datasets
curated using novel strategies, including AudioSkills-XL, LongAudio-XL,
AF-Think, and AF-Chat, and train AF3 with a novel five-stage curriculum-based
training strategy. Trained on only open-source audio data, AF3 achieves new
SOTA results on over 20+ (long) audio understanding and reasoning benchmarks,
surpassing both open-weight and closed-source models trained on much larger
datasets.
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Arushi Goel
687486d6257d4f0435370302
Sreyan Ghosh
claimed_verified
2025-07-15T19:10:32.937Z
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/avatars/ca23ecdec2d31c99ecce97d9b180ae0c.svg
Ghosh
user
Sreyan88
687486d6257d4f0435370303
Jaehyeon Kim
687486d6257d4f0435370304
Sonal Kumar
687486d6257d4f0435370305
Zhifeng Kong
687486d6257d4f0435370306
Sang-gil Lee
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Chao-Han Huck Yang
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Ramani Duraiswami
687486d6257d4f0435370309
Dinesh Manocha
687486d6257d4f043537030a
Rafael Valle
687486d6257d4f043537030b
Bryan Catanzaro
Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large
  Audio Language Models
We present Audio Flamingo 3 (AF3), a fully open state-of-the-art (SOTA) large
audio-language model that advances reasoning and understanding across speech,
sound, and music. AF3 introduces: (i) AF-Whisper, a unified audio encoder
trained using a novel strategy for joint representation learning across all 3
modalities of speech, sound, and music; (ii) flexible, on-demand thinking,
allowing the model to do chain-of-thought-type reasoning before answering;
(iii) multi-turn, multi-audio chat; (iv) long audio understanding and reasoning
(including speech) up to 10 minutes; and (v) voice-to-voice interaction. To
enable these capabilities, we propose several large-scale training datasets
curated using novel strategies, including AudioSkills-XL, LongAudio-XL,
AF-Think, and AF-Chat, and train AF3 with a novel five-stage curriculum-based
training strategy. Trained on only open-source audio data, AF3 achieves new
SOTA results on over 20+ (long) audio understanding and reasoning benchmarks,
surpassing both open-weight and closed-source models trained on much larger
datasets.
Audio Flamingo 3, a state-of-the-art audio-language model, advances reasoning and understanding across speech, sound, and music through a unified audio encoder and novel training strategies.
audio encoder joint representation learning chain-of-thought-type reasoning multi-turn chat long audio understanding voice-to-voice interaction AudioSkills-XL LongAudio-XL AF-Think AF-Chat curriculum-based training