═══════════════════════════════════════════════════════════════════════════════ SMOOTHMIX ANIMATIONS LTX ═══════════════════════════════════════════════════════════════════════════════ ─────────────────────────────────────────────────────────────────────────────── IDENTITY ─────────────────────────────────────────────────────────────────────────────── Base model LTX-2.3 Generation mode Text-to-Video (T2V), Image-to-Video (I2V) Checkpoint not determined — verify before use Category Visual style Author DigitalPastel Source https://civitai.com/models/2524245 Provenance CivitAI · model 2524245 · version 2837052 ─────────────────────────────────────────────────────────────────────────────── WEIGHTS ─────────────────────────────────────────────────────────────────────────────── File SmoothMix_Animations_LTX2.safetensors Version v1.0 Size 1,285.6 MB Format SafeTensor / unknown precision SHA256 02a9e8d1884db23e022828f7d7221d5c93fc3c8d7924a022d8e4ab0a81ebb31f Published unknown ─────────────────────────────────────────────────────────────────────────────── TRIGGER WORDS ─────────────────────────────────────────────────────────────────────────────── › "smoothmixanime" › "anime style" › "smoothmixrealism" › "realistic style" ─────────────────────────────────────────────────────────────────────────────── RECOMMENDED SETTINGS ─────────────────────────────────────────────────────────────────────────────── The author did not publish specific settings. No author settings were published. Community baseline: steps Distilled path (all six official ComfyUI LTX-2.3 templates): 8 steps in stage 1 driven by an explicit ManualSigmas list "1.0, 0.99375, 0.9875, 0.98125, 0.975, 0.909375, 0.725, 0.421875, 0.0", then 3 steps in the stage-2 refine after the x2 latent upscale ("0.85, 0.7250, 0.4219, 0.0") — verified by reading the template JSONs. The ic_lora template instead uses a plain KSampler at 8 steps. The Python DistilledPipeline is documented as "8 predefined sigmas (8 steps in stage 1, 4 steps in stage 2)". Full/dev model with real guidance: Lightricks' own single-stage example workflow sets LTXVScheduler to 15 steps., cfg 1.0 for anything running the distilled checkpoint or the distilled LoRA — CFGGuider is set to 1 in both stages of every official ComfyUI template (verified in the JSONs), the ic_lora template's KSampler is cfg 1, and a note in Lightricks' own two- stage workflow reads "Do explore various samplers and cfg values (although we advise them to be kept close to 1)". For the guided full-model path, Lightricks' single-stage workflow uses MultimodalGuider with per-modality GuiderParameters: VIDEO cfg 3 (rescale 0.9), AUDIO cfg 7 (rescale 0.7). Treat 3 as the video anchor since that is the official value., sampler euler with SamplerCustomAdvanced + ManualSigmas is the default in the ComfyUI templates; the flf2v template uses SamplerEulerAncestral and the ic_lora template a plain KSampler with euler_ancestral + linear_quadratic. Lightricks' own example workflows use euler_ancestral_cfg_pp (single stage) and euler_cfg_pp (two stage). TI2VidTwoStagesHQPipeline swaps in the second-order res_2s sampler for fewer steps., resolution Generate low, then upscale. ComfyUI templates set EmptyLTXVLatentVideo to 768x512 / 97 frames and target 1280x720 (with a 1920x1088 resize and a 1536-long-edge resize in the chain), using LTXVLatentUpsampler with ltx-2.3-spatial- upscaler-x2-1.1.safetensors. Lightricks' own example workflows use 960x544 / 121 frames with the same x2 upscaler. Hard constraints from the model card: width and height must be divisible by 32, and frame count must be divisible by 8 plus 1 (97, 121, 193...). Frame rate: LTXVConditioning is 24 in the t2v/id_lora templates and 25 in the ic_lora/flf2v templates; CreateVideo is 24 in the ComfyUI templates. The x2 temporal upscaler is described in the model card as being for higher FPS., lora_strength Official distilled/acceleration LoRA: 0.5 in every ComfyUI template (LoraLoaderModelOnly), 0.5 plus a 0.2 second branch in Lightricks' single- stage example workflow, and 0.8 in the ltx-pipelines README/installation CLI example (--distilled-lora 0.8). Official IC- LoRA Union-Control and ID-LoRA: 1.0 in the templates. Community norm for content/style LoRAs: the IC-LoRA Dual-Character author states 0.6-1.0 used alone, dropped to 0.3-0.5 when stacked with other LoRAs.. ─────────────────────────────────────────────────────────────────────────────── ADOPTION & POPULARITY ─────────────────────────────────────────────────────────────────────────────── No statistics available. ─────────────────────────────────────────────────────────────────────────────── COMMUNITY NOTES ─────────────────────────────────────────────────────────────────────────────── 16 comment(s) on the source listing; showing 5. [+11] EDIT: Effect is quite strong. Tricky to tune down. Because LTX-2.3 is only one model versus Wan's double pass, it's hard to use this supplementally - the look wants to be pretty prominent. Looking forward to trying this. Your Wan LoRA is one of the best. But holy hell have I had a rough time with LTX-2.3. When it works, it's neat, but so many duff generations. Hit rate is like... 1 in 10? 1 in 20? [+16] I had to rent a rtx pro 6000 on runpod to be able to train my loras. If I trained locally it was going to take 48 HOURS to do 1 epoch. Runpod took 6 hours. Ltx takes ALOT to train it hit 94gb of VRAM and like 130gb of ram use on runpod I do not have pockets deep enough for a rig like that running locally lmao. From my experience ltx needs alot of videos. My motion lora took 155 videos that were al • Thanks for your hard work. I haven't tried it yet. Would you consider making a ko fi support page at some point? • 30 hours, lol this looks great i clearly need to rethink because 30 hours is basically just starting ._. • The LTX 2.3 is still very raw. The sound seems to have been improved. But otherwise, it's terrible. Archive summary: SmoothMix Animations LTX is a style LoRA designed for LTX Video-family checkpoints, published by [DigitalPastel](/users/DigitalPastel) on CivitAI in April 2026. It layers on top of any compatible LTX Video checkpoint. You load the checkpoint first, then apply this LoRA on top of it. It has attracted 3,734 downloads. The model is flagged NSFW on CivitAI and can produce explicit content. Source: https://civarchive.com/models/2524245?modelVersionId=2837052 Comments are other users' words, reproduced as written. ─────────────────────────────────────────────────────────────────────────────── CHAINING / STACKING ─────────────────────────────────────────────────────────────────────────────── Stacks with others not stated The author gave no chaining guidance. The rules below are the general LTX-2.3 ones, not anything specific to this LoRA. General LTX-2.3 rules that apply here (see REFERENCE.txt): • Stacking an acceleration LoRA with a task LoRA is officially sanctioned: the ID-LoRA template chains LoraLoaderModelOnly(ltx_2.3_22b _distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16, 0.5) into LoraLoaderModelOnly(ltx-2.3-id-lora-talkvid-3k, 1.0) on the dev checkpoint. • The Python CLI exposes `--lora [strength]` as a repeatable flag with default strength 1.0, so multiple adapters at once is a supported configuration, not a hack. • Load the acceleration/distilled LoRA on the dev checkpoint only. The two-stage pipelines require it for the full model but explicitly do not use it for DistilledPipeline, ICLoraPipeline or DubItPipeline, which already run distilled weights. • Do not stack two distillation LoRAs (e.g. the official rank-384 / rank-111 one plus a community DMD LoRA). The DaSiWa DMD LoRA already blends 75-80% of the official distilled delta into its audio-output route and is described by its author as recreating the distilled model on top of stock dev, i.e. a replacement. • IC-LoRAs are not chained like ordinary LoRAs: each carries a reference_downscale_factor in its safetensors metadata and needs a node that reads it (GetICLoRAParameters -> LTXVAddGuide in core, or LTXICLoRALoaderModelOnly + LTXAddVideoICLoRAGuide in ComfyUI-LTXVideo). Without one the factor silently defaults to 1. • Two IC-LoRA reference guides can be driven from a single IC-LoRA: the CrossView Warp author wires both a depth-warp video and the original video into separate reference guides and sets latent_downscale_factor = 1 on both. • DubItPipeline accepts exactly one Dub-It IC-LoRA (`--lora` exactly once) and applies it in both stages — that path is single-adapter by design. • Community convention on strengths when stacking: the IC-LoRA Dual- Character author recommends 0.6-1.0 for a content LoRA used alone, dropped to 0.3-0.5 when combined with others. • Some LoRA pairs are designed to be blended against each other — the LTX 2.3 Crisp Enhance / Soft Enhance pair is described by its author as "can be used together and balanced at different strengths". • The gemma-3-12b-it-abliterated LoRA is not a video LoRA and does not belong in the DiT chain — it patches the Gemma text encoder through a model+clip LoraLoader, as the official templates wire it. • The author never states which weight family this targets. Within LTX-2.3, dev vs distilled is low risk: they are the same architecture and the distillation itself is published as a LoRA that the model card calls "applicable to the full model", so ordinary content LoRAs load on both. Expect style/strength drift rather than breakage; the ─────────────────────────────────────────────────────────────────────────────── PROS ─────────────────────────────────────────────────────────────────────────────── + Well established — 3,733 downloads. [source: CivitAI stats] + Positively received — 281 thumbs-up, 1 down. [source: CivitAI stats] + Explicit trigger word(s) — smoothmixanime, anime style, smoothmixrealism, realistic style — so the effect can be turned on and off from the prompt. [source: model metadata] + Author documents use across several modes (T2V, I2V). [source: description] ─────────────────────────────────────────────────────────────────────────────── CONS & CAVEATS ─────────────────────────────────────────────────────────────────────────────── - Large at 1286 MB — slower to load and heavier to stack. [source: file size] - Thin documentation — expect trial and error. [source: description length] ─────────────────────────────────────────────────────────────────────────────── COMPATIBILITY WARNING ─────────────────────────────────────────────────────────────────────────────── Within LTX-2.3, dev vs distilled is low risk: they are the same architecture and the distillation itself is published as a LoRA that the model card calls "applicable to the full model", so ordinary content LoRAs load on both. Expect style/strength drift rather than breakage; the distilled LoRA is meant to be applied to a dev checkpoint, not stacked on an already-distilled one (the Python pipelines that start from a distilled checkpoint — DistilledPipeline, ICLoraPipeline, DubItPipeline — explicitly do not take --distilled-lora). The genuine risk is cross-version and cross- format, and it is silent rather than a hard error: the LTX-2 repo README states flatly that files "are not interchangeable between the two models, and a LoRA only works with the model it was trained on", and a wrong- version LoRA surfaces only as a stream of "lora key not loaded: diffusion_model...." console warnings while generation proceeds as if no LoRA were attached. The same silent no-op hits correctly-versioned LoRAs saved in a non-ComfyUI key layout: SimpleTuner issue #2349 shows keys like diffusion_model.connectors.audio_connector.transformer_blocks.N.attn1.to_q going unloaded, where the LTX-2 trainer's own layout is attn1/attn2 for video, audio_attn1/audio_attn2 for audio and audio_to_video_attn / video_to_audio_attn for cross-modal. Community finetunes (Sulphur 2, JoyAI- Echo merges) load stock LTX-2.3 LoRAs but shift the result. And an IC-LoRA loaded without a metadata-reading node loses its reference scale: ComfyUI's GetICLoRAParameters reads reference_downscale_factor out of the LoRA's safetensors metadata and silently falls back to 1 when it is absent, so a ref0.5 IC-LoRA wired straight into LTXVAddGuide without it feeds the reference at the wrong latent scale. ─────────────────────────────────────────────────────────────────────────────── AUTHOR'S DESCRIPTION ─────────────────────────────────────────────────────────────────────────────── (the author left no description) ─────────────────────────────────────────────────────────────────────────────── EXAMPLE MEDIA ─────────────────────────────────────────────────────────────────────────────── 6 preview(s) in ./example_images/ — community results for this LoRA. Videos keep a matching _poster.jpg still frame. No prompts are recorded below: CivitAI's public API flags these posts as having generation metadata but does not return it, so the prompts cannot be scraped. Open the model page to read them. 01_video.mp4 (video, 704x1280) still: 01_poster.jpg 02_video.mp4 (video, 704x1280) still: 02_poster.jpg 03_video.mp4 (video, 704x1280) still: 03_poster.jpg 04_video.mp4 (video, 960x960) still: 04_poster.jpg 05_video.mp4 (video, 768x1152) still: 05_poster.jpg 06_video.mp4 (video, 768x1152) still: 06_poster.jpg ─────────────────────────────────────────────────────────────────────────────── HOW TO USE (COMFYUI) ─────────────────────────────────────────────────────────────────────────────── 1. Update ComfyUI. LTX-2.3 is supported in ComfyUI core (comfy_extras/nodes_lt.py provides EmptyLTXVLatentVideo, LTXVAddGuide, GetICLoRAParameters, LTXVConditioning, LTXVScheduler, LTXVConcatAVLatent/LTXVSeparateAVLatent, LTXVReferenceAudio and more) and the six official templates need no custom nodes; install the Lightricks "ComfyUI-LTXVideo" custom node pack only if you want IC-LoRA loaders, low- VRAM loaders, HDR decode, audio-only nodes or Q8 nodes. 2. Put the base checkpoint in ComfyUI/models/checkpoints/ — ltx-2.3-22b-dev-fp8.safetensors (29.15 GB) or ltx-2.3-22b-distilled- fp8.safetensors (29.53 GB) from Lightricks/LTX-2.3-fp8, or the bf16 originals (46.15 GB) from Lightricks/LTX-2.3. It is a single file that also carries the video VAE, the audio VAE and the text projection. 3. Put gemma_3_12B_it_fp4_mixed.safetensors in ComfyUI/models/text_encoders/ (from Comfy-Org/ltx-2). The Python package instead wants the full google/gemma-3-12b-it-qat-q4_0-unquantized folder. 4. Put ltx-2.3-spatial-upscaler-x2-1.1.safetensors in ComfyUI/models/latent_upscale_models/ (needed by every two-stage template), and moge_2_vitl_normal_fp16.safetensors (Comfy-Org/MoGe) in ComfyUI/models/geometry_estimation/ if you use the IC-LoRA depth path. 5. Put every LoRA .safetensors in ComfyUI/models/loras/. Subfolders are fine — Lightricks' own workflows reference "ltxv/ltx2/ltx-2.3-22b-distilled-lora-384-1.1.safetensors". 6. Load a normal content/style LoRA with LoraLoaderModelOnly, wired between CheckpointLoaderSimple's MODEL output and the guider/sampler. In the stock templates you chain it after the distilled-LoRA loader. Use the full LoraLoader (model + clip) only for the gemma-3-12b-it-abliterated LoRA, which patches the Gemma text encoder rather than the video model. 7. On a dev checkpoint, also load the acceleration LoRA (ltx_2.3_22b_distilled_1.1_lora_dynamic_fro09_avg_rank_111_bf16.safetensors at 0.5) unless you intend to run the slow guided path. 8. For an IC-LoRA, the LoRA loader alone is not enough: either use LTXICLoRALoaderModelOnly + LTXAddVideoICLoRAGuide (ComfyUI-LTXVideo), or — as the official ic_lora template does — feed the LoRA-loaded model through core's GetICLoRAParameters into LTXVAddGuide, so the reference_downscale_factor stored in the file's safetensors metadata is read instead of defaulting to 1. 9. Template Library > Video > any LTX-2.3 workflow gives you correct wiring to start from; workflow JSONs are at Comfy-Org/workflow_templates/templates /video_ltx2_3_{t2v,i2v,ia2v,flf2v,ic_lora,id_lora}.json and Lightricks/ComfyUI-LTXVideo/example_workflows/2.3/. ─────────────────────────────────────────────────────────────────────────────── Scraped by lorakit on 2026-09-05 03:47 UTC. Stats and description are the author's; pros/cons are derived from the evidence tagged beside each line. ───────────────────────────────────────────────────────────────────────────────