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KXSR Cinematic Chase Concept WAN 14B + 1.3B T2V

7669°
KXSR Cinematic Chase Concept WAN 14B + 1.3B T2V
Created by
Kytra
on Civitai
by Kytra - Example Prompts kxsr, A futuristic car, resembling a DeLorean with neon accents, drives quickly through a desert landscape with planets in the sky. The driver wears VR goggles. The car transitions to a convertible, passes a green screen, and eventually floats over a lake with neon rings, showcasing a blend of futuristic and surreal elements.
Creator notes
KXSR Cinematic Chase Concept LorA for WAN 2.1 14B and 1.3B T2V In collaboration with [ Labs presents: This LoRA enables the creation of cinematic sequences featuring characters and imaginative scenery with fast-paced high-octane 'vehicle' chase scene action. The typical view will be from a near-isometric perspective with dynamic movement in horizontal aspect ratio generation. Can still create fun results at other aspect ratios/resolutions. Use the trigger word "kxsr" to activate the model's specialized training. Prompt Format kxsr, [describe the vehicle] [ACTION-VERB HERE: rides/drives/speeds/drifts/etc] quickly, [describe the driver/characters/scene/environment of the world and other actions happening around them] Example Prompts kxsr, A futuristic car, resembling a DeLorean with neon accents, drives quickly through a desert landscape with planets in the sky. The driver wears VR goggles. The car transitions to a convertible, passes a green screen, and eventually floats over a lake with neon rings, showcasing a blend of futuristic and surreal elements. ======================================= kxsr, A vintage army jeep with two soldiers driving quickly through a flower-filled field. The driver is shooting at a dragonfly with a rider on it. Bullets fly as the dragonfly evades. The house in the background is surrounded by a garden of flowers. Recommended Settings - CFG: 5.0 - Shift value: 4.0 - LoRA strength: 1.0 - ~73 frames - 720x1280 horizontal aspect ratio Technical Details - Base model: WAN 2.1 14B + 1.3B Text2Video - Training dataset: 98 clips - Resolution: 1280 x 720 (horizontal format) - Frame count: 73 frames per clip - For optimal results, maintain these specifications during inference This LoRA works best when you provide detailed descriptions of both the subject and the surrounding environment while following the prescribed format. Screenshot shows my typical inference testing setup for lora evals:
Trigger words
kxsr
241 downloads · 25 likes on Civitai
SHA256
8F894622C6B0C5D24FCD6C9F4D30D8B03E6DB7A5683F9732E0B7A1DB44E936D2
Ranking badge
Updated Oct 22, 2026
KXSR Cinematic Chase Concept WAN 14B + 1.3B T2V on ModelTrends.ai: Heat 7,669°
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KXSR Cinematic Chase Concept WAN 14B + 1.3B T2V Popularity Trend
Heat score, last 12 months
Heat score
7,669°
This week
n/a
Wasn't released/tracked
This month
n/a
Wasn't released/tracked
Past year
n/a
Wasn't released/tracked
KXSR Cinematic Chase Concept WAN 14B + 1.3B T2V: Heat score, last 12 months7,000°7,260°7,519°7,779°8,038°Oct 2025Dec 2025Mar 2026May 2026Aug 2026Oct 20267,669°ModelTrends.ai
7,000°
Floor
The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.
+715°
Civitai downloads
241 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.
+212°
Likes
25 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.
−258°
Age
−258° because the Wan weights came out in 2025. Every model inherits the age of the weights it is built on: 150° a year, up to 750°, and it keeps growing until then. Without it the top of the list would be 2022 and 2023 checkpoints on the strength of downloads that had years to pile up.
Show detailed breakdown
Every number on this site can be checked. This model's heat score is 7,669°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.
  1. 1
    Start at the floor.
    Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
    7,000°
    running total
  2. 2
    Add the downloads.
    241 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
    +715°
    7,715°
    running total
  3. 3
    Add the likes.
    25 likes and thumbs up, at half the weight of a download.
    +212°
    7,927°
    running total
  4. 4
    Take off the age.
    The Wan weights came out in 2025: 150° a year, up to 750°, growing until then.
    −258°
    7,669°
    running total
  5. =
    The heat score.
    Where this model stands on every list of this site. Nothing else adjusts it.
    7,669°
Glossary: the terms used here
Heat score
One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor
The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents
Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale
Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes
Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate
How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated
Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
Seeder
Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde
A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites
Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens
A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
Full model (checkpoint)
The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding
Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
Family and weights
The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
Age
Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
Family boost
A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
Stand-in score
A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
New! (grace period)
A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
Trend
How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model
The middle of the catalog: half the models with a figure grew faster over the period, half slower.
How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.
Example renders
Prompts and settings shared by the people who made these renders on Civitai. Pick a render to see how it was made.
Render by Kytra on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Size
1280x720
Prompt
kxsr, A surreal, fantastical scene unfolds with a strange, green, slug-like creature gliding through an alien landscape. Floating green orbs with pink tails drift around it. The creature has large, iridescent eyes and a fringe of dark tendrils. The background features bizarre, tree-like structures with holes and pink, web-like growths. The creature moves rapidly, creating a sense of speed and otherworldly wonder.
Render by Kytra on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Size
1280x720
Prompt
kxsr, A stylized 3D animation showcases a red, propeller-driven vehicle with a green-skinned character and a wood log cargo, racing across a desert landscape. A detached, drone-like device accompanies it. The vehicle kicks up dust as it passes a steampunk-style city with clock towers and industrial structures, firing projectiles. The scene transitions to a close-up, revealing the vehicles details and the citys whimsical architecture under a vibrant blue sky with fluffy clouds.
Render by kengnologo55 on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Guidance
4
Seed
250600358
Size
480x848
Weight used
1
Prompt
A surreal landscape pulses faintly in the background while a lone figure stands still, sensing the strange quiet before collapse. Subtle camera drift, soft quantum distortion effects. --slow cinematic motion --dark tone --ar 9:16
Render by Kytra on
Civitai
·
Prompt on BunchaPrompts
Flag
Settings
Size
1280x720
Prompt
kxsr, A cartoonish 3D animation unfolds on a sunny beach, featuring a muscular, dark-skinned character with a red and yellow helmet, riding a whimsical, red and yellow watercraft with a large, fan-like propeller. The propeller spins, creating visual effects of motion. The character and vehicle move through turquoise water, past orange and white buoys, towards a green, mountainous island under a blue sky with scattered clouds. A seagull flies overhead, adding to the lively, tropical scene.
Run Locally
kxsr_WAN1-3B_cinematic_chase.safetensors
167 MB · SafeTensor
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Torrents
kxsr_WAN1-3B_cinematic_chase.safetensors
166.95 MB · WAN 1.3B T2V · 0 seeders ·
CivitasBay
kxsr_WAN14B_cinematic_chase_v1.safetensors
292.59 MB · WAN 14B T2V · 0 seeders ·
CivitasBay
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