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Add Dispatch Style Lora LTX2.3
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DISPATCH STYLE LORA LTX2.3
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IDENTITY
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Base model LTX-2.3
Generation mode not declared by the author
Checkpoint not determined β€” verify before use
Category Visual style
Author tazmannner379
Source https://civitai.com/models/2375591
Provenance CivitAI Β· model 2375591 Β· version 2776562
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WEIGHTS
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File dispatch23_v1_2-step00031000.comfy.safetensors
Version LTX 2.3 V1.1
Size 1,285.6 MB
Format SafeTensor / unknown precision
SHA256 54c9119f9f9f41dca49a00ff734c0020a90b38d1e15e62bca77ed50b84d2e4b6
Published 2026-03-16
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TRIGGER WORDS
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β€Ί "DISPSTYLE"
β€Ί "char_rr"
β€Ί "char_bb"
β€Ί "char_case"
β€Ί "char_invisi"
β€Ί "char_prism"
β€Ί "char_malev"
β€Ί "char_roy"
β€Ί "char_punchup"
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RECOMMENDED SETTINGS
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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") β€” 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 β€” 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 <path> 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..
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ADOPTION & POPULARITY
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Downloads 2,212
Rating 100% positive (150/150)
Comments 17
Published 173 days ago
Download rate 7.7/day since release
Adoption rank #20 of 150 in this collection (High)
Momentum rank #43 of 150 by download rate (Steady)
Adoption tier is the percentile of total downloads within this collection;
momentum is the percentile of downloads-per-day since release. Momentum is
ranked rather than measured against a fixed rate, because this base model
is itself new and every LoRA looks fast on an absolute scale. Both numbers
are CivitAI's, read on the scrape date at the foot of this file.
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CHAINING / STACKING
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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):
β€’ 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.
β€’ The Python CLI exposes `--lora <path> [strength]` as a repeatable flag
with default strength 1.0, so multiple adapters at once is a supported
configuration, not a hack.
β€’ 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.
β€’ 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.
β€’ 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.
β€’ 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.
β€’ DubItPipeline accepts exactly one Dub-It IC-LoRA (`--lora` exactly
once) and applies it in both stages β€” that path is single-adapter by
design.
β€’ 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.
β€’ Some LoRA pairs are designed to be blended against each other β€” the LTX
2.3 Crisp Enhance / Soft Enhance pair is described by its author as
"can be used together and balanced at different strengths".
β€’ The gemma-3-12b-it-abliterated LoRA is not a video LoRA and does not
belong in the DiT chain β€” it patches the Gemma text encoder through a
model+clip LoraLoader, as the official templates wire it.
β€’ 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
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PROS
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+ Well established β€” 2,212 downloads. [source: CivitAI stats]
+ Positively received β€” 150 thumbs-up with no down-votes. [source:
CivitAI stats]
+ Explicit trigger word(s) β€” DISPSTYLE, char_rr, char_bb, char_case,
char_invisi, char_prism, char_malev, char_roy, char_punchup β€” so the
effect can be turned on and off from the prompt. [source: model
metadata]
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CONS & CAVEATS
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- Author never states which generation mode it was trained for; test
against your own workflow before relying on it. [source: description]
- Large at 1286 MB β€” slower to load and heavier to stack. [source: file
size]
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COMPATIBILITY WARNING
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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 β€” DistilledPipeline, ICLoraPipeline, DubItPipeline β€” 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.
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AUTHOR'S DESCRIPTION
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This is just the same dataset but trained for LTX 2.3 but I increased rank
from 32 to 64 (thus the 1.2GB file size). The result is really great. We
get 6 character likeness and voices which sound and look great. For one
lora that's a lot of information! And the characters don't bleed into
eachother.
Edit: All issues have been fixed in v1.1. Give it a try!
Add "subtitle text" to negatives if you get them, you should not get them
otherwise.
Robert, Invisigal, Blonde Blazer (and without powers too), Prism, Malevola,
Chase
Punchup is trained but not enough data, haven't tested. (char_punchup)
Royd is in the data as char_roy but also not much data.
Other characters are in the dataset but not tagged. Shroud is not in the
data at all.v1.0
Style Trigger:
DISPSTYLE
Invisigal :
char_invisi, a woman with short dark hair accented by a purple streak,
wearing a purple jacket over a dark top and distressed black jeans
Blonde Blazer:
char_bb is a woman with long blonde hair and a blue mask, wearing a blue
and yellow superhero suit with a yellow cape and a red diamond-shaped gem
on her chest.
(no costume, powerless)
char_bb has long, wavy dark brown hair and wears a strapless evening dress
with long dark blue opera gloves
Robert Robertson:
char_rr has short brown hair and wears a light blue button-down shirt with
the sleeves rolled up to his elbows and dark trousers.
Prism: char_prism, She is a black woman with straight hair split down the
middle, teal on the viewer's left and magenta on the right. She wears
large, rectangular, reflective teal visors, blue lipstick, and a gold ring
necklace. Her attire consists of a black sleeveless top, thick gold bands
on her upper arms, a long magenta glove on her left arm, and a teal glove
on her right hand
Malevola:
char_malev a woman with red skin, long black horns, and glowing yellow
eyes, a long red tail,, is dressed in a white tank top and denim shorts.
she has a sword attached to her back.
Chase:
char_chase, an older Black man with white hair in locs and a mustache,
wears a yellow sweater over a light blue collared shirt and black trousers
with a gold buckle belt. A pair of glasses hangs from the collar of his
sweater.
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VERSION NOTES
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Fixed the issue with the dataset causing visi and bb's voice to merge. I
added in an additional 100 or so missing video clips of visi and around 30
more of bb. Also I fixed some bad captions. Then I resumed from 24.5k steps
and trained to 31k steps.
The result is much better voices for the two. I missed a few captions on
rr's beard so if you see stubble on female characters just put "stubble" in
the negative prompt. Also roy and punchup's voice and likeness is slightly
better now. But still not stable. Overall very good result. I'm really
proud of this one.
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EXAMPLE MEDIA
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6 preview(s) in ./example_images/ β€” 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, 1920x1024)
still: 01_poster.jpg
02_video.mp4 (video, 1920x1024)
still: 02_poster.jpg
03_video.mp4 (video, 1920x1024)
still: 03_poster.jpg
04_video.mp4 (video, 1920x1024)
still: 04_poster.jpg
05_video.mp4 (video, 1920x1024)
still: 05_poster.jpg
06_video.mp4 (video, 1920x1024)
still: 06_poster.jpg
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HOW TO USE (COMFYUI)
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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/ β€”
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 β€” 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 β€”
as the official ic_lora template does β€” 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/.
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Scraped by lorakit on 2026-09-04 23:14 UTC.
Stats and description are the author's; pros/cons are derived from the
evidence tagged beside each line.
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