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LTX-2-19B-dev-FP8

2026-05-03 模型 0 743
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信息属性
  • 名称
  • ltx-2-19b-dev-fp8
  • 类型
  • 音视频同步
  • 软件
  • ComfyUI
  • 文件大小
  • 25.22GB
详情介绍

ltx-2-19b-dev-fp8AI 音视频生成模型:

LTX-2-19B-dev-FP8 模型典型应用场景

它是高质量文生视频 / 图生视频模型,主打长时长、高画质、音画同步,FP8 量化后更适合本地 / 小显存部署,适用场景非常偏向内容创作、短视频、营销、影视辅助等方向。

1. 短视频与自媒体创作

  • 文字直接生成剧情短片、风景动态视频、搞笑段子、知识科普动画
  • 单张图片生成动态壁纸、人物微动、场景动效
  • 快速批量产出抖音、快手、小红书竖屏短视频

2. 广告与营销物料

  • 品牌宣传短片、产品展示动态视频
  • 电商主图视频、商品动态演示
  • 活动海报→一键生成动态海报视频

3. 影视 / 动画前期预演

  • 剧本分镜快速可视化
  • 概念短片、预告片小样生成
  • 场景、特效、镜头运镜的低成本测试

4. 游戏与虚拟内容

  • 游戏宣传动态 PV、场景漫游视频
  • NPC 动态展示、剧情过场动画初稿
  • 虚拟主播背景动态视频

5. 教育与培训内容

  • 课件动态演示、微课视频
  • 安全培训、操作流程演示视频
  • 无需拍摄即可制作教学短片

6. 个人创意与 AIGC 创作

  • 小说 / 故事可视化动态短片
  • 照片复活、老照片动态化
  • 音乐可视化、随节奏生成画面

7. 设计与视觉行业

  • 平面设计稿→动态视觉效果
  • 室内 / 建筑效果图生成漫游视频
  • 插画、原画转为动态短片

它最突出的优势场景

  1. 需要较长视频(相对普通文生视频模型)
  2. 追求画质接近真实 / 电影感
  3. 希望音画一起生成,不用后期配音效
  4. 本地部署、不想依赖云端 API
  5. 显存有限但想跑大参数量视频模型(FP8 量化优势)

简单总结:

凡是需要 “动起来的画面”,且不想真人拍摄、不想复杂剪辑的场景,它都能用。

安装说明:

一、先准备好硬件

  • 显卡显存:≥16GB(24GB 更稳)
  • 内存:≥32GB(推荐 64GB)
  • 硬盘:至少 50GB 空闲 SSD

二、安装插件(必须)

打开 ComfyUI 管理器:
  1. 安装 ComfyUI-LTXVideo 插件
  2. 重启 ComfyUI
如果没有管理器,手动克隆:
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custom_nodes/ComfyUI-LTXVideo

三、模型文件放哪里

把这些文件放到对应目录:

1. LTX-2 19B FP8 主模型

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models/ltx_video/ltx-2-19b-dev-fp8.safetensors

2. VAE

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models/vae/ltx_vae.safetensors

3. T5 文本编码器

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models/clip/t5xxl_fp8_e4m3.safetensors

4. 音频模型(可选)

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models/audio_models/lm_small_v1.safetensors
models/audio_models/vocoder_v1.safetensors

四、直接可用的 ComfyUI 工作流(复制即用)

把下面整段复制,直接粘贴到 ComfyUI 空白画布,会自动加载节点:
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{"last_node_id":29,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[29,85],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[399,84],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[761,85],"size":[322,130],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["A beautiful landscape, cinematic, 4K, detailed, realistic, smooth motion"]},{"id":4,"type":"LTXEmptyLatentVideo","pos":[28,291],"size":[240,100],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"LATENT","type":"LATENT","links":[6],"shape":3}],"properties":{"Node name for S&R":"LTXEmptyLatentVideo"},"widgets_values":[768,512,16]},{"id":5,"type":"LTXSampler","pos":[397,289],"size":[324,260],"flags":{},"order":4,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",14,6.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","disable"]},{"id":6,"type":"VTAEDecode","pos":[398,579],"size":[240,100],"flags":{},"order":5,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":7}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[8],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":7,"type":"PreviewVideo","pos":[700,580],"size":[240,260],"flags":{},"order":6,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":8}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideo"},"widgets_values":["ltx_output","video/mp4",1]}],"links":[[2,1,0,5,0],[3,2,0,3,0],[4,1,1,5,1],[5,3,0,5,2],[6,4,0,5,3],[7,5,0,6,1],[8,6,0,7,0]],"groups":[],"config":{},"extra":{},"version":0.4}

五、关键参数说明

  • 分辨率:
    • 16G 显存:768×512
    • 24G 显存:896×512 / 1024×576
  • 帧数:16 帧最稳(≈2 秒)
  • CFG:6.5
  • 步数:14–20

六、显存不够的解决办法

  1. 开启 FP8
  2. 分辨率降到 640×448
  3. 帧数改为 8 帧
  4. 关闭 highres fix
  5. 关闭其他占用显存的程序
中文提示词模板 + 图生视频工作流 + 带音频的完整音视频流,全部适配 ltx-2-19b-dev-fp8,复制粘贴就能用。

一、中文提示词模板(电影感 / 古风 / 写实 / 游戏)

复制到 LTXTextEncode 正面提示词即可,CFG 6.0–7.0 效果最好。

1. 电影感大片

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宏大电影场景,史诗级光影,大气运镜,细腻皮肤质感,真实布料纹理,4K超高清,动态流畅,专业摄影,浅景深,cinematic,sharp focus,masterpiece,best quality

2. 古风仙侠

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古风仙侠女子,飘逸白衣,长发随风飘动,云雾缭绕山间,花瓣飞舞,水墨国风,柔和光影,仙气飘飘,唯美意境,流畅动态,东方美学,精致细节,4K

3. 写实生活 / 人物

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真实人物,自然表情,细腻皮肤,自然光,窗边柔和光线,真实质感,流畅微表情,自然动作,生活化场景,高清细节,realistic,photorealistic

4. 游戏 CG / 科幻

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科幻未来城市,飞行器穿梭,霓虹灯光,赛博朋克,金属质感,粒子特效,宏大场景,流畅运镜,电影级CG,high detail,unreal engine 5

负面通用(必加)

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模糊,失真,抖动,变形,低清,马赛克,文字,水印,丑陋,畸形,扭曲,多余肢体,坏脸,坏手,lowres,blurry,ugly,disfigured

二、图生视频工作流(ComfyUI 直接粘贴)

用于:一张图片 → 生成流畅视频
plaintext
{"last_node_id":35,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[49,69],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[419,68],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[781,69],"size":[322,140],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["A beautiful landscape, cinematic, 4K, detailed, realistic, smooth motion"]},{"id":4,"type":"LoadImage","pos":[39,261],"size":[310,280],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[6],"shape":3}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["【替换你的图片】","image"]},{"id":5,"type":"LTXImageToVideoLatent","pos":[397,260],"size":[324,120],"flags":{},"order":4,"mode":0,"inputs":[{"name":"IMAGE","type":"IMAGE","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXImageToVideoLatent"},"widgets_values":[16]},{"id":6,"type":"LTXSampler","pos":[398,409],"size":[324,260],"flags":{},"order":5,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":7}],"outputs":[{"name":"LATENT","type":"LATENT","links":[8],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",14,6.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","disable"]},{"id":7,"type":"VTAEDecode","pos":[399,699],"size":[240,100],"flags":{},"order":6,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":8}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[9],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":8,"type":"PreviewVideo","pos":[701,700],"size":[240,260],"flags":{},"order":7,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":9}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideo"},"widgets_values":["ltx_img2vid","video/mp4",1]}],"links":[[2,1,0,6,0],[3,2,0,3,0],[4,1,1,6,1],[5,3,0,6,2],[6,4,0,5,0],[7,5,0,6,3],[8,6,0,7,1],[9,7,0,8,0]],"groups":[],"config":{},"extra":{},"version":0.4}

三、带音频生成的完整音视频工作流(最终完整版)

视频 + 背景音乐 / 环境音 一起生成,直接复制到 ComfyUI
plaintext
{"last_node_id":45,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[39,49],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[409,48],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[771,49],"size":[322,140],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["Cinematic scene, realistic, smooth motion, detailed atmosphere"]},{"id":4,"type":"LTXEmptyLatentVideo","pos":[38,241],"size":[240,100],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"LATENT","type":"LATENT","links":[6],"shape":3}],"properties":{"Node name for S&R":"LTXEmptyLatentVideo"},"widgets_values":[768,512,16]},{"id":5,"type":"LTXSampler","pos":[407,240],"size":[324,260],"flags":{},"order":4,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",14,6.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","disable"]},{"id":6,"type":"VTAEDecode","pos":[408,529],"size":[240,100],"flags":{},"order":5,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":7}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[8],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":9,"type":"LTXAudioLM","pos":[38,620],"size":[310,140],"flags":{},"order":6,"mode":0,"inputs":[],"outputs":[{"name":"AUDIO_LM","type":"AUDIO_MODEL","links":[10],"shape":3}],"properties":{"Node name for S&R":"LTXAudioLM"},"widgets_values":["lm_small_v1.safetensors"]},{"id":10,"type":"LTXVocoder","pos":[39,770],"size":[310,140],"flags":{},"order":7,"mode":0,"inputs":[],"outputs":[{"name":"VOCODER","type":"AUDIO_MODEL","links":[11],"shape":3}],"properties":{"Node name for S&R":"LTXVocoder"},"widgets_values":["vocoder_v1.safetensors"]},{"id":11,"type":"LTXGenerateAudio","pos":[408,640],"size":[310,140],"flags":{},"order":8,"mode":0,"inputs":[{"name":"AUDIO_LM","type":"AUDIO_MODEL","link":10},{"name":"VOCODER","type":"AUDIO_MODEL","link":11}],"outputs":[{"name":"AUDIO","type":"AUDIO","links":[12],"shape":3}],"properties":{"Node name for S&R":"LTXGenerateAudio"},"widgets_values":["atmospheric cinematic background music, calm, immersive",16]},{"id":12,"type":"PreviewVideoAudio","pos":[771,530],"size":[280,300],"flags":{},"order":9,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":8},{"name":"audio","type":"AUDIO","link":12}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideoAudio"},"widgets_values":["ltx_av_output","video/mp4",1]}],"links":[[2,1,0,5,0],[3,2,0,3,0],[4,1,1,5,1],[5,3,0,5,2],[6,4,0,5,3],[7,5,0,6,1],[8,6,0,12,0],[10,9,0,11,0],[11,10,0,11,1],[12,11,0,12,1]],"groups":[],"config":{},"extra":{},"version":0.4}

四、使用要点(16GB 显存必看)

  • 分辨率:768×512
  • 帧数:16 帧(约 2 秒)
  • 步数:14 步
  • CFG:6.5
  • 模型必须放对路径:
    • models/ltx_video/ltx-2-19b-dev-fp8.safetensors
    • models/clip/t5xxl_fp8_e4m3.safetensors
    • models/vae/ltx_vae.safetensors
    • 音频:models/audio_models/
  • 超低显存优化版(12GB 也能跑)

  • 一、12GB 显存也能跑的核心参数(必设)

    • 分辨率:640 × 384
    • 帧数:8 帧(≈1 秒)
    • 采样步数:12 步
    • CFG:5.0
    • 采样器:euler
    • 调度:normal
    16GB 显存可以用:704 × 400 / 10 帧

    二、ComfyUI 启动参数(关键!省显存)

    启动 ComfyUI 时加上这些参数:
    plaintext
    --fp8-upcast
    --lowvram
    --cpu-offload
    --dont-upcast-attention
    
    能再省 2~3GB 显存。

    三、超低显存专用工作流(复制即用)

    plaintext
    {"last_node_id":30,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[29,85],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[399,84],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[761,85],"size":[322,130],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["A beautiful landscape, cinematic, 4K, detailed, realistic, smooth motion"]},{"id":4,"type":"LTXEmptyLatentVideo","pos":[28,291],"size":[240,100],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"LATENT","type":"LATENT","links":[6],"shape":3}],"properties":{"Node name for S&R":"LTXEmptyLatentVideo"},"widgets_values":[640,384,8]},{"id":5,"type":"LTXSampler","pos":[397,289],"size":[324,260],"flags":{},"order":4,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",12,5.0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","enable"]},{"id":6,"type":"VTAEDecode","pos":[398,579],"size":[240,100],"flags":{},"order":5,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":7}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[8],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":7,"type":"PreviewVideo","pos":[700,580],"size":[240,260],"flags":{},"order":6,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":8}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideo"},"widgets_values":["ltx_lowvram","video/mp4",1]}],"links":[[2,1,0,5,0],[3,2,0,3,0],[4,1,1,5,1],[5,3,0,5,2],[6,4,0,5,3],[7,5,0,6,1],[8,6,0,7,0]],"groups":[],"config":{},"extra":{},"version":0.4}
    

    四、图生视频低显存版

    plaintext
    {"last_node_id":36,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[49,69],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[419,68],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[781,69],"size":[322,140],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["A beautiful landscape, cinematic, 4K, detailed, realistic, smooth motion"]},{"id":4,"type":"LoadImage","pos":[39,261],"size":[310,280],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[6],"shape":3}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["your_image.png","image"]},{"id":5,"type":"LTXImageToVideoLatent","pos":[397,260],"size":[324,120],"flags":{},"order":4,"mode":0,"inputs":[{"name":"IMAGE","type":"IMAGE","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXImageToVideoLatent"},"widgets_values":[8]},{"id":6,"type":"LTXSampler","pos":[398,409],"size":[324,260],"flags":{},"order":5,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":7}],"outputs":[{"name":"LATENT","type":"LATENT","links":[8],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",12,5.0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","enable"]},{"id":7,"type":"VTAEDecode","pos":[399,699],"size":[240,100],"flags":{},"order":6,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":8}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[9],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":8,"type":"PreviewVideo","pos":[701,700],"size":[240,260],"flags":{},"order":7,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":9}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideo"},"widgets_values":["ltx_img2vid_lowvram","video/mp4",1]}],"links":[[2,1,0,6,0],[3,2,0,3,0],[4,1,1,6,1],[5,3,0,6,2],[6,4,0,5,0],[7,5,0,6,3],[8,6,0,7,1],[9,7,0,8,0]],"groups":[],"config":{},"extra":{},"version":0.4}
    

    五、带音频的低显存版

    plaintext
    {"last_node_id":46,"nodes":[{"id":1,"type":"LTXLoadModel","pos":[39,49],"size":[322,170],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"MODEL","type":"MODEL","links":[2],"shape":3},{"name":"VAE","type":"VAE","links":[4],"shape":3}],"properties":{"Node name for S&R":"LTXLoadModel"},"widgets_values":["ltx-2-19b-dev-fp8.safetensors","ltx_vae.safetensors"]},{"id":2,"type":"LTXLoadTextEncoder","pos":[409,48],"size":[322,130],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"TEXT_ENCODER","type":"CLIP","links":[3],"shape":3}],"properties":{"Node name for S&R":"LTXLoadTextEncoder"},"widgets_values":["t5xxl_fp8_e4m3.safetensors"]},{"id":3,"type":"LTXTextEncode","pos":[771,49],"size":[322,140],"flags":{},"order":2,"mode":0,"inputs":[{"name":"text_encoder","type":"CLIP","link":3}],"outputs":[{"name":"CONDITIONING","type":"CONDITIONING","links":[5],"shape":3}],"properties":{"Node name for S&R":"LTXTextEncode"},"widgets_values":["Cinematic scene, realistic, smooth motion, detailed atmosphere"]},{"id":4,"type":"LTXEmptyLatentVideo","pos":[38,241],"size":[240,100],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"LATENT","type":"LATENT","links":[6],"shape":3}],"properties":{"Node name for S&R":"LTXEmptyLatentVideo"},"widgets_values":[640,384,8]},{"id":5,"type":"LTXSampler","pos":[407,240],"size":[324,260],"flags":{},"order":4,"mode":0,"inputs":[{"name":"model","type":"MODEL","link":2},{"name":"vae","type":"VAE","link":4},{"name":"positive","type":"CONDITIONING","link":5},{"name":"latent_video","type":"LATENT","link":6}],"outputs":[{"name":"LATENT","type":"LATENT","links":[7],"shape":3}],"properties":{"Node name for S&R":"LTXSampler"},"widgets_values":["euler","normal",12,5.0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,"fixed","enable"]},{"id":6,"type":"VTAEDecode","pos":[408,529],"size":[240,100],"flags":{},"order":5,"mode":0,"inputs":[{"name":"vae","type":"VAE","link":4},{"name":"samples","type":"LATENT","link":7}],"outputs":[{"name":"VIDEO","type":"IMAGE","links":[8],"shape":3}],"properties":{"Node name for S&R":"VTAEDecode"},"widgets_values":["default"]},{"id":9,"type":"LTXAudioLM","pos":[38,620],"size":[310,140],"flags":{},"order":6,"mode":0,"inputs":[],"outputs":[{"name":"AUDIO_LM","type":"AUDIO_MODEL","links":[10],"shape":3}],"properties":{"Node name for S&R":"LTXAudioLM"},"widgets_values":["lm_small_v1.safetensors"]},{"id":10,"type":"LTXVocoder","pos":[39,770],"size":[310,140],"flags":{},"order":7,"mode":0,"inputs":[],"outputs":[{"name":"VOCODER","type":"AUDIO_MODEL","links":[11],"shape":3}],"properties":{"Node name for S&R":"LTXVocoder"},"widgets_values":["vocoder_v1.safetensors"]},{"id":11,"type":"LTXGenerateAudio","pos":[408,640],"size":[310,140],"flags":{},"order":8,"mode":0,"inputs":[{"name":"AUDIO_LM","type":"AUDIO_MODEL","link":10},{"name":"VOCODER","type":"AUDIO_MODEL","link":11}],"outputs":[{"name":"AUDIO","type":"AUDIO","links":[12],"shape":3}],"properties":{"Node name for S&R":"LTXGenerateAudio"},"widgets_values":["atmospheric cinematic background music, calm, immersive",8]},{"id":12,"type":"PreviewVideoAudio","pos":[771,530],"size":[280,300],"flags":{},"order":9,"mode":0,"inputs":[{"name":"video","type":"IMAGE","link":8},{"name":"audio","type":"AUDIO","link":12}],"outputs":[],"properties":{"Node name for S&R":"PreviewVideoAudio"},"widgets_values":["ltx_av_lowvram","video/mp4",1]}],"links":[[2,1,0,5,0],[3,2,0,3,0],[4,1,1,5,1],[5,3,0,5,2],[6,4,0,5,3],[7,5,0,6,1],[8,6,0,12,0],[10,9,0,11,0],[11,10,0,11,1],[12,11,0,12,1]],"groups":[],"config":{},"extra":{},"version":0.4}
    

    六、必开的显存优化开关

    在 LTXSampler 里:
    • Offload:enable(必须开)
    • Dtype:FP8
    • 不要开任何增强、高清修复
  • 一、原生支持 FP8 加速(推荐,速度最快)

    这类显卡硬件级支持 FP8 计算,加载与推理最稳、速度最快。

    消费级 / 工作站

    • RTX 5090 / 5080 / 5070 Ti(32GB/24GB/16GB)
    • RTX 4090 / 4090 Ti / 4080 Ti / 4080 Super(24GB/24GB/20GB/16GB)
    • RTX A6000 / A6000 Ada / A5000 / A4500(48GB/48GB/24GB/24GB)
    • RTX 4070 Ti Super / 4070 Ti / 4070 Super(16GB/12GB/12GB)

    数据中心 / 专业卡

    • H100 / H200 / L40S / L40
    • A100 80GB / A100 40GB(部分驱动 / 框架支持)

    最低显存门槛

    • 原生 FP8 流畅跑:≥ 24GB 显存(4090/5090/A6000 等)
    • 优化后可跑:≥ 16GB 显存(4070 Ti Super/4080 Super 等,需开 offload + 低分辨率 / 低帧数)

    二、兼容运行(无原生 FP8,但可强制加载)

    30 系列及更早显卡不支持硬件 FP8,但可通过软件模拟 / 精度转换运行,速度慢、显存占用高、易报错

    可兼容列表

    • RTX 3090 / 3090 Ti / 3080 Ti / 3080(24GB/24GB/12GB/10GB)
    • RTX A10 / A30 / A40(24GB/24GB/48GB)
    • RTX 2080 Ti / Titan RTX(11GB/24GB,仅极限精简版)

    兼容条件

    • 显存 ≥ 12GB(仅 8 帧 / 640×384 极限精简)
    • 必须开启:--fp8-upcast + --lowvram + --cpu-offload
    • 只能用 distilled-fp8 蒸馏版,不建议用 dev-fp8 完整版

    三、不支持(无法运行)

    • RTX 2070 及以下(显存<10GB,无 FP8 兼容)
    • AMD 显卡(ROCm 对 LTX-2 FP8 支持极差,几乎无法跑)
    • Intel Arc 显卡(驱动与框架暂不支持 LTX-2 FP8 推理)
    • 笔记本独显(RTX 4060 及以下,8GB 显存):仅能跑 distilled-fp4,无法跑 dev-fp8

    四、显卡选择速查表(按体验排序)

    表格
    显卡 显存 FP8 支持 跑 dev-fp8 体验
    RTX 5090 / A6000 32GB/48GB ✅ 原生 流畅,1024×576 / 16 帧
    RTX 4090 / 4090 Ti 24GB ✅ 原生 流畅,768×512 / 16 帧
    RTX 4080 Ti / 4080 Super 20GB/16GB ✅ 原生 良好,640×384 / 8–12 帧
    RTX 4070 Ti Super 16GB ✅ 原生 一般,640×384 / 8 帧
    RTX 3090 / 3090 Ti 24GB ❌ 软件模拟 慢,易 OOM,仅低分辨率
    RTX 3080 Ti / 3080 12GB/10GB ❌ 软件模拟 极慢,仅极限精简

    五、快速判断你的显卡

    1. 看型号:40/50 系列 Ada 架构 → 优先选
    2. 看显存:≥ 24GB → 原生流畅;16GB → 优化可跑;<12GB → 不建议
    3. 看架构:Ampere(30 系)及更早 → 仅兼容,体验差
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