LTX-2: Efficient Joint Audio-Visual Foundation Model
Recent text-to-video diffusion models can generate compelling video sequences, yet they remain silent -- missing the semantic, emotional, and atmospheric cues that audio provides. We introduce LTX-2, an open-source foundational model capable of generating high-quality, temporally synchronized audiovisual content in a unified manner. LTX-2 consists of an asymmetric dual-stream transformer with a 14B-parameter video stream and a 5B-parameter audio stream, coupled through bidirectional audio-video cross-attention layers with temporal positional embeddings and cross-modality AdaLN for shared timestep conditioning. This architecture enables efficient training and inference of a unified audiovisual model while allocating more capacity for video generation than audio generation. We employ a multilingual text encoder for broader prompt understanding and introduce a modality-aware classifier-free guidance (modality-CFG) mechanism for improved audiovisual alignment and controllability. Beyond generating speech, LTX-2 produces rich, coherent audio tracks that follow the characters, environment, style, and emotion of each scene -- complete with natural background and foley elements. In our evaluations, the model achieves state-of-the-art audiovisual quality and prompt adherence among open-source systems, while delivering results comparable to proprietary models at a fraction of their computational cost and inference time. All model weights and code are publicly released.
695dc6d9c03d6d81e4399e85
Yoav HaCohen
admin_assigned
2026-01-07T13:19:29.722Z
6303cc5e0547362a22a51af0
/avatars/8f3348f121565bf6c5e1af0e559a43a3.svg
Yoav HaCohen
yoavhacohen
user
yoavhacohen
695dc6d9c03d6d81e4399e86
Benny Brazowski
admin_assigned
2026-01-07T13:19:35.981Z
6489c487b9e9258ba065418f
https://cdn-avatars.huggingface.co/v1/production/uploads/6489c487b9e9258ba065418f/6rzmV3bQ3YxswG6NP2hDW.png
Benny Brazowski
benibraz
user
benibraz
695dc6d9c03d6d81e4399e87
Nisan Chiprut
admin_assigned
2026-01-07T13:19:41.634Z
62dd30a8d43078cd49ac8ad8
/avatars/ad599719290637f7817b7508a91c2e2c.svg
Nisan Chiprut
nisan
user
nisan
695dc6d9c03d6d81e4399e88
Yaki Bitterman
admin_assigned
2026-01-07T13:19:46.749Z
64a7adc087cbd4dc7301fdd6
/avatars/b4ec4c3a0409af8ec4a5de05db453034.svg
Yaki Bitterman
jacobitterman
user
jacobitterman
695dc6d9c03d6d81e4399e89
Andrew Kvochko
admin_assigned
2026-01-07T13:19:51.722Z
65897258509bcae23fa162c9
/avatars/29d277a0c425c936e25e82e79caa10a4.svg
Andrew Kvochko
kvochko
user
kvochko
695dc6d9c03d6d81e4399e8a
Avishai Berkowitz
695dc6d9c03d6d81e4399e8b
Daniel Shalem
695dc6d9c03d6d81e4399e8c
Daphna Lifschitz
admin_assigned
2026-01-07T13:20:04.180Z
681af83e2f4aaa88639e703d
/avatars/d69b664daad0afb529440c14fdb9bc3a.svg
Daphna Lifschitz
Daphnal
user
Daphnal
695dc6d9c03d6d81e4399e8d
Dudu Moshe
admin_assigned
2026-01-07T13:20:13.512Z
636b97a57631fe5e86fe1fa2
/avatars/c568ae26fd4fc2655cd12f15d539db58.svg
Dudu Moshe
dudumoshe
user
dudumoshe
695dc6d9c03d6d81e4399e8e
Eitan Porat
695dc6d9c03d6d81e4399e8f
Eitan Richardson
admin_assigned
2026-01-07T13:20:22.677Z
677a422979d3c32a5dd87a0a
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/WUa6E68GpnT2mEMJ41nDd.png
Eitan Richardson
eitanrich
user
eitanrich
695dc6d9c03d6d81e4399e90
Guy Shiran
admin_assigned
2026-01-07T13:20:28.250Z
673f6911d83832a6ce15e7bf
/avatars/0da6cded3b0e785241a6ba5fdb5d8ceb.svg
Guy Shiran
guysrn
user
guysrn
695dc6d9c03d6d81e4399e91
Itay Chachy
admin_assigned
2026-01-07T13:20:36.781Z
65744a2fe09de6aa74026d80
https://cdn-avatars.huggingface.co/v1/production/uploads/65744a2fe09de6aa74026d80/kCxIKdeBJwAPKmvlm7fDP.jpeg
Itay Chachy
ItayChachy
user
ItayChachy
695dc6d9c03d6d81e4399e92
Jonathan Chetboun
695dc6d9c03d6d81e4399e93
Michael Finkelson
admin_assigned
2026-01-07T13:20:53.574Z
6678365ac411b340b32d6148
https://cdn-avatars.huggingface.co/v1/production/uploads/6678365ac411b340b32d6148/7OhHzbu65pa95eYrAbbLW.jpeg
Michael Finkelson
MichaelFinkelson
user
MichaelFinkelson
695dc6d9c03d6d81e4399e94
Michael Kupchick
admin_assigned
2026-01-07T13:20:59.945Z
6318aa43cb4ca740c4c55651
/avatars/24082c776d284393a5a38a99e5c0bab8.svg
michael kupchick
michaellightricks
user
michaellightricks
695dc6d9c03d6d81e4399e95
Nir Zabari
admin_assigned
2026-01-07T13:21:07.297Z
673f29b568595672b8d3e90e
https://cdn-avatars.huggingface.co/v1/production/uploads/673f29b568595672b8d3e90e/4sYADg3mpqMKmJ4fQwaTl.png
Nir Zabari
NirZabariLTX
user
NirZabariLTX
695dc6d9c03d6d81e4399e96
Nitzan Guetta
admin_assigned
2026-01-07T13:21:14.712Z
64ae89c043dda9449a1eb1ba
/avatars/12cf3de929d38ddd92cc3f3337dc2ed2.svg
Nitzan Guetta
nitzanguetta
user
nitzanguetta
695dc6d9c03d6d81e4399e97
Noa Kotler
695dc6d9c03d6d81e4399e98
Ofir Bibi
admin_assigned
2026-01-07T13:21:27.196Z
631f58935ba8c026340b377c
https://cdn-avatars.huggingface.co/v1/production/uploads/631f58935ba8c026340b377c/4yoHLdNE99VBb7ji_Mzzj.jpeg
Ofir Bibi
ofirbibi
user
ofirbibi
695dc6d9c03d6d81e4399e99
Ori Gordon
admin_assigned
2026-01-07T13:21:34.878Z
674348b46215a2c0878e219b
/avatars/8a213e431a1583d1a93377410907c059.svg
Ori Gordon
origordon
user
origordon
695dc6d9c03d6d81e4399e9a
Poriya Panet
695dc6d9c03d6d81e4399e9b
Roi Benita
695dc6d9c03d6d81e4399e9c
Shahar Armon
695dc6d9c03d6d81e4399e9d
Victor Kulikov
695dc6d9c03d6d81e4399e9e
Yaron Inger
695dc6d9c03d6d81e4399e9f
Yonatan Shiftan
695dc6d9c03d6d81e4399ea0
Zeev Melumian
695dc6d9c03d6d81e4399ea1
Zeev Farbman
LTX-2: Efficient Joint Audio-Visual Foundation Model
Recent text-to-video diffusion models can generate compelling video sequences, yet they remain silent -- missing the semantic, emotional, and atmospheric cues that audio provides. We introduce LTX-2, an open-source foundational model capable of generating high-quality, temporally synchronized audiovisual content in a unified manner. LTX-2 consists of an asymmetric dual-stream transformer with a 14B-parameter video stream and a 5B-parameter audio stream, coupled through bidirectional audio-video cross-attention layers with temporal positional embeddings and cross-modality AdaLN for shared timestep conditioning. This architecture enables efficient training and inference of a unified audiovisual model while allocating more capacity for video generation than audio generation. We employ a multilingual text encoder for broader prompt understanding and introduce a modality-aware classifier-free guidance (modality-CFG) mechanism for improved audiovisual alignment and controllability. Beyond generating speech, LTX-2 produces rich, coherent audio tracks that follow the characters, environment, style, and emotion of each scene -- complete with natural background and foley elements. In our evaluations, the model achieves state-of-the-art audiovisual quality and prompt adherence among open-source systems, while delivering results comparable to proprietary models at a fraction of their computational cost and inference time. All model weights and code are publicly released.
LTX-2 is an open-source audiovisual diffusion model that generates synchronized video and audio content using a dual-stream transformer architecture with cross-modal attention and classifier-free guidance.
text-to-video diffusion models audiovisual content dual-stream transformer cross-attention layers temporal positional embeddings AdaLN classifier-free guidance modality-aware classifier-free guidance multilingual text encoder diffusion models