# LTX-2 by LTX.io: Open-Weight Model Source: https://savrn.com/models/ltx-2-2 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## 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](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 18.9 GB | 22.7 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 9.4 GB | 11.3 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/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](https://savrn.com/ai-index/pricing/gpus), read Oct 24, 2026. [LTX-2 on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/ltx-2-2/gpus) ## 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](https://huggingface.co/Lightricks/LTX-2) Released by LTX.io through its official repository on Hugging Face. [Read the license](https://github.com/Lightricks/LTX-2/blob/main/LICENSE). ## Built From - Described by [arXiv:2601.03233](https://savrn.com/papers/ltx-2-efficient-joint-audio-visual-foundation-model) ## 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. ## Built on This Model - Adapter of[LTX-2-AVCReward-LoRA](https://savrn.com/models/ltx-2-avcreward-lora) - Derived from[LTX-2-AVCReward-LoRA](https://savrn.com/models/ltx-2-avcreward-lora) ## 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. ## Similar Models Model · Image to video ### [WorldCrafter-Base](https://savrn.com/models/worldcrafter-base) [ARC Lab, Tencent](https://savrn.com/model-publishers/tencentarc) Base transformer weights and their matching camera adapter and LoRA for the WorldCrafter inference code. Place this directory beside WorldCrafter-Fast. Base reads the following shared folders from Fast: repencoder/, textencoder/, tokenizer/, vae/, and scheduler/. Base does not need Fast's transformer or adapter folders. The relative path is configured in inferenceconfig.json. Keep the Base-specific transformer/ and adapter/ together. SHA256SUMS covers the packaged Base files; shared component hashes are recorded in Fast's package. 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If your research or project builds upon Wan2.1 or Wan2.2, we welcome you to share it with us so we can highlight it for the broader community. - Wan2.2 Text-to-Video - [x]… Open weights apache-2.0 14.3B parameters diffusers [View model](https://savrn.com/models/wan2-2-14b-i2v-480p-lightning-nsfw-diffusers) Model · Image to video ### [LTX-Video](https://savrn.com/models/ltx-video) [LTX.io](https://savrn.com/model-publishers/lightricks) This model card focuses on the model associated with the LTX-Video model, codebase available here. LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 30 FPS videos at a 1216×704 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content. You can use the model for purposes under the license: - 2B version 0.9: license - 2B version 0.9.1 license - 2B version 0.9.5 license - 2B version 0.9.6-dev license - 2B version 0.9.6-distilled license - 13B version 0.9.7-dev license - 13B version 0.9.7-dev-fp8 license… Open weights other 1.9B parameters diffusers [View model](https://savrn.com/models/ltx-video) Model · Image to video ### [Wan_2.2_ComfyUI_Repackaged](https://savrn.com/models/wan-2-2-comfyui-repackaged) [Comfy Org](https://savrn.com/model-publishers/comfy-org) Repackaged model files for ComfyUI. - https://huggingface.co/nvidia/ChronoEdit-14B-Diffusers - https://huggingface.co/Wan-AI/Wan2.2-Animate-14B - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control-Camera - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control - https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-Control - https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-InP - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP - https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B - https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B - https://huggingface.co/Wan-AI/Wan2.2-S2V-14B - https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B - https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B… Open weights apache-2.0 diffusion-single-file [View model](https://savrn.com/models/wan-2-2-comfyui-repackaged) Model · Image to video ### [Wan-2.2](https://savrn.com/models/wan-2-2) [Comfy Org](https://savrn.com/model-publishers/comfy-org) Repackaged model files for ComfyUI. - https://huggingface.co/nvidia/ChronoEdit-14B-Diffusers - https://huggingface.co/Wan-AI/Wan2.2-Animate-14B - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control-Camera - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control - https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-Control - https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-InP - https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP - https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B - https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B - https://huggingface.co/Wan-AI/Wan2.2-S2V-14B - https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B - https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B… Open weights apache-2.0 diffusion-single-file [View model](https://savrn.com/models/wan-2-2) Model · Image to video ### [LTX-2.5](https://savrn.com/models/ltx-2-5) [LTX.io](https://savrn.com/model-publishers/lightricks) LTX-2.5 is an open world model with open weights, built for local execution and fine-tuning. Its established use is generating synchronized, high-fidelity video and audio from text, image, and video inputs; applicability to emerging domains such as robotics and physical AI is developing. Full control and customization — self-host on your own infrastructure. No per-generation billing, no per-seat lock-in, no forced API dependency. Revenue is measured across the whole entity, including subsidiaries and affiliates under common control. The full, binding terms live in LICENSE. - Native multishot generation — generate connected scenes in a single pass: multiple shots that hold character… Access requested at publisher other diffusion-single-file [View model](https://savrn.com/models/ltx-2-5) ## LTX.io [All models and datasets](https://savrn.com/model-publishers/lightricks) ## Versions - [dfcc2108383f](https://savrn.com/models/ltx-2-2/versions/dfcc2108383f) · current 2026-09-18 ## Explore More - [All image to video models](https://savrn.com/models/tasks/image-to-video) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-20. - [Hugging Face record](https://huggingface.co/Lightricks/LTX-2) - [How the hub is built](https://savrn.com/model-hub/methodology)