LTX-2 by LTX.io: Open-Weight Model

Runs On

What it takes to serve LTX-2 (18.9B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

Precision	Weights	Memory needed	Cheapest setup	Per hour	Also fits
16-bit	37.8 GB	45.3 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00
8-bit	18.9 GB	22.7 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00
4-bit	9.4 GB	11.3 GB	1x MI300X (192 GB) Vultr	$1.85	1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 9, 2026.

LTX-2 on every accelerator the SAVRN Index prices, at every precision

SAVRN's Notes on LTX-2

Video with its own soundtrack is the job here. LTX-2 generates picture and audio together in one 18.9 billion parameter model, and the publisher's set runs to 69 files and 314 GB once the distilled and upscaler variants are counted. At 16-bit the weights are 37.8 GB and need about 45.3 GB in use, so one MI300X with 192 GB, at $1.85 an hour on-demand, carries it with room left over. At 8-bit the need drops to 22.7 GB, and at 4-bit to 11.3 GB.

The license is filed as other, with no summary in our record, so read the publisher's terms before a commercial run; they cover the full, distilled and upscaler models and any derivatives. No host on the SAVRN Index sells it by the token, so $1.85 an hour is the only price reference. The paper is arXiv:2601.03233. Released January 3, 2026, last updated August 4, 2026.

SAVRN Research, 2026-09-18

Model Card

This model card focuses on the LTX-2 model, as presented in the paper LTX-2: Efficient Joint Audio-Visual Foundation Model. The codebase is available here. LTX-2 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model. It brings together the core building blocks of modern video generation, with open weights and a focus on practical, local execution. LTX-2 is accessible right away via the following links: You can use the models - full, distilled, upscalers and any derivatives of the models - for purposes under the license. We recommend you use the built-in LTXVideo nodes that can be found in the ComfyUI Manager. For manual…

Excerpt from the card by LTX.io, licensed other.

Identity and Version

Repository: Lightricks/LTX-2
Publisher: LTX.io
Task: Image to video
Modality: Other
Library: diffusers
Parameters: 18.9B parameters
Languages: en, de, es, fr, ja, ko, zh, it
Revision: dfcc2108383fe1aaa0584bdf55d368a4bdadd90c
First published: 2026-01-03
Last updated: 2026-08-04

Files and Weights

69 files, 314.3 GB in total. The weights are 44 files totalling 314.3 GB in safetensors.

Weights44 files · 314.3 GB

Configuration17 files · 646.4 KB

Tokenizer3 files · 39.2 MB

Documentation2 files · 31.0 KB

Other2 files · 15.7 MB

Repository1 file · 1.6 KB

Every file

File	Type	Size	SHA-256
audio_vae/diffusion_pytorch_model.safetensors	Weights	106.5 MB	b36ce4066065
connectors/diffusion_pytorch_model.safetensors	Weights	2.9 GB	c7c0ad36c2d0
latent_upsampler/diffusion_pytorch_model.safetensors	Weights	995.7 MB	c56276acbffb
ltx-2-19b-dev-fp4.safetensors	Weights	20.0 GB	08a28245d841
ltx-2-19b-dev-fp8.safetensors	Weights	27.1 GB	8a67e709b6d1
ltx-2-19b-dev.safetensors	Weights	43.3 GB	4a51e70aad66
ltx-2-19b-distilled-fp8.safetensors	Weights	27.1 GB	8ae14327130c
ltx-2-19b-distilled-lora-384.safetensors	Weights	7.7 GB	2718f8958200
ltx-2-19b-distilled.safetensors	Weights	43.3 GB	c4006d689061
ltx-2-spatial-upscaler-x2-1.0.safetensors	Weights	995.8 MB	3160fabf8edf
ltx-2-temporal-upscaler-x2-1.0.safetensors	Weights	262.0 MB	9a35c2eb92f6
text_encoder/diffusion_pytorch_model-00001-of-00012.safetensors	Weights	1.7 GB	06ffef2cbc99
text_encoder/diffusion_pytorch_model-00002-of-00012.safetensors	Weights	5.0 GB	308270af3b7c
text_encoder/diffusion_pytorch_model-00003-of-00012.safetensors	Weights	4.8 GB	523d1b6d3ba4
text_encoder/diffusion_pytorch_model-00004-of-00012.safetensors	Weights	5.0 GB	cf426cf00fe6
text_encoder/diffusion_pytorch_model-00005-of-00012.safetensors	Weights	4.9 GB	01c8cec1fc6d
text_encoder/diffusion_pytorch_model-00006-of-00012.safetensors	Weights	5.0 GB	f1a5ec996bdd
text_encoder/diffusion_pytorch_model-00007-of-00012.safetensors	Weights	4.9 GB	5594441c5b83
text_encoder/diffusion_pytorch_model-00008-of-00012.safetensors	Weights	5.0 GB	b333d3bb4764
text_encoder/diffusion_pytorch_model-00009-of-00012.safetensors	Weights	4.9 GB	34db39ec863e
text_encoder/diffusion_pytorch_model-00010-of-00012.safetensors	Weights	5.0 GB	0e72953188ec
text_encoder/diffusion_pytorch_model-00011-of-00012.safetensors	Weights	5.0 GB	29993bd9711e
text_encoder/diffusion_pytorch_model-00012-of-00012.safetensors	Weights	589.9 MB	19a8f0f23c87
text_encoder/model-00001-of-00011.safetensors	Weights	1.7 GB	cbc6e8132e49
text_encoder/model-00002-of-00011.safetensors	Weights	5.0 GB	b95e7ab472b8
text_encoder/model-00003-of-00011.safetensors	Weights	4.8 GB	3731e7c18280
text_encoder/model-00004-of-00011.safetensors	Weights	5.0 GB	e9d1ce8b472f
text_encoder/model-00005-of-00011.safetensors	Weights	4.9 GB	cb478659a67b
text_encoder/model-00006-of-00011.safetensors	Weights	5.0 GB	a190581d8719
text_encoder/model-00007-of-00011.safetensors	Weights	4.9 GB	c347de789ff3
text_encoder/model-00008-of-00011.safetensors	Weights	5.0 GB	2ec7525b89b0
text_encoder/model-00009-of-00011.safetensors	Weights	4.9 GB	2b0117ecf1d8
text_encoder/model-00010-of-00011.safetensors	Weights	5.0 GB	d9f665a74358
text_encoder/model-00011-of-00011.safetensors	Weights	2.7 GB	999bf4706d4f
transformer/diffusion_pytorch_model-00001-of-00008.safetensors	Weights	5.0 GB	c4cebec5231d
transformer/diffusion_pytorch_model-00002-of-00008.safetensors	Weights	5.0 GB	fbbcbd973b51
transformer/diffusion_pytorch_model-00003-of-00008.safetensors	Weights	5.0 GB	2767c94f485e
transformer/diffusion_pytorch_model-00004-of-00008.safetensors	Weights	5.0 GB	54598964c133
transformer/diffusion_pytorch_model-00005-of-00008.safetensors	Weights	5.0 GB	2eb2b5aa625a
transformer/diffusion_pytorch_model-00006-of-00008.safetensors	Weights	4.9 GB	068c360cde8b
transformer/diffusion_pytorch_model-00007-of-00008.safetensors	Weights	5.0 GB	a55908e7fde1
transformer/diffusion_pytorch_model-00008-of-00008.safetensors	Weights	2.9 GB	8a7e2d0941dc
vae/diffusion_pytorch_model.safetensors	Weights	2.4 GB	107cc359e3c4
vocoder/diffusion_pytorch_model.safetensors	Weights	111.2 MB	15855fc59233
audio_vae/config.json	Configuration	505 B	—
connectors/config.json	Configuration	649 B	—
latent_upsampler/config.json	Configuration	266 B	—
model_index.json	Configuration	616 B	—
scheduler/scheduler_config.json	Configuration	487 B	—
text_encoder/config.json	Configuration	3.0 KB	—
text_encoder/diffusion_pytorch_model.safetensors.index.json	Configuration	150.0 KB	—
text_encoder/generation_config.json	Configuration	168 B	—
text_encoder/model.safetensors.index.json	Configuration	108.6 KB	—
tokenizer/added_tokens.json	Configuration	35 B	—
tokenizer/preprocessor_config.json	Configuration	570 B	—
tokenizer/processor_config.json	Configuration	70 B	—
tokenizer/special_tokens_map.json	Configuration	662 B	—
transformer/config.json	Configuration	1.1 KB	—
transformer/diffusion_pytorch_model.safetensors.index.json	Configuration	377.7 KB	—
vae/config.json	Configuration	1.3 KB	—
vocoder/config.json	Configuration	544 B	—
LICENSE	Documentation	21.5 KB	—
README.md	Documentation	9.6 KB	—
ltx-2-running-local.mp4	Other	15.7 MB	8c0bde52079d
tokenizer/chat_template.jinja	Other	1.5 KB	—
.gitattributes	Repository	1.6 KB	—
tokenizer/tokenizer.json	Tokenizer	33.4 MB	4667f2089529
tokenizer/tokenizer.model	Tokenizer	4.7 MB	1299c11d7cf6
tokenizer/tokenizer_config.json	Tokenizer	1.2 MB	—

License and Download

License: other
Access: Open weights, no gate
Download size: 314.3 GB

Download from LTX.io

Released by LTX.io through its official repository on Hugging Face. Read the license.

Built From

Described by arXiv:2601.03233

Memory Requirements

Precision	Weights in memory
As published	314.3 GB
16-bit	37.8 GB
8-bit	18.9 GB
4-bit	9.4 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About LTX-2

How much GPU memory does LTX-2 need?

About 45.3 GB at 16-bit and 11.3 GB at 4-bit: the weights (18.9B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run LTX-2 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

What license is LTX-2 released under?

other, as its publisher declares it. Read the license text before commercial use.

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