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360 degree panoramic shot LTX 2.3

8130°
360 degree panoramic shot   LTX 2.3
Created by
Ragamuffin20
on Civitai
by Ragamuffin20 - 360-degree panoramic shot - LTX-2
Creator notes
Convert flat videos to VR workflow: THE SEEM ISSUE HAS BEEN FIXED: When I realized LTX-2 can generate 4K video, my first thought was: holy shit, we can finally start pumping out VR videos. So I immediately rushed to make this LoRA without really thinking it through, just to see whether LTX-2 could already do this by default. Short answer: kind of. Much like the Hardcut LoRA for Wan 2.2, LTX-2 understands the concept of 360° video, but struggles to execute it properly. This LoRA gives it the extra push it needs to reliably generate true 360-degree content without turning into a mangled mess. That said, for whatever reason, it does not seamlessly close the seam, so there’s a noticeable vertical line in the 360 sphere when you turn around. I’m not sure if a node exists that can fix this yet, but please let me know if you find a solution. Note: the video ends are matching they just cut off and slightly different points so technically you could crop the video horizontally so it ends on one side exactly where it starts on another. Anyway, as always, if you like what I do and want to support the work, feel free to buy me a coffee ☕ or support me on patreon Recommended Settings - Weight: 0.6–1 works well - I’ve even gotten away with 0.2, so feel free to experiment - Aspect Ratio: 2:1 Post-Processing (Optional) The raw video can be played in most 360 media players or VR players as-is. However, if you want actual depth in VR, you’ll need to apply Stereoscopic depth to the video. This node can do that: ⚠️ Warning: It appears to have a size limit. For example, one of my videos ended up around 500 MB, which exceeds what the node (and even ComfyUI itself) will accept for upload. If you find a workaround, please let me know. Otherwise, you’ll need to use an external depth tool or handle the depth manually. VR Metadata Injection (Highly Recommended) It’s also a good idea to inject VR metadata so headsets and players automatically recognize the video as VR content. You can use Google’s Spatial Media tool for this: It’s free and very easy to use. TL;DR - Yes, it works - Use 2:1 aspect ratio - You can make VR videos - You can make them better by adding depth and VR metadata Extra Banter Honestly, I’m kind of glad LTX-2 can’t do this out of the box. I was already a full day into training this LoRA before I realized I probably should’ve checked that first. More importantly, I now fully understand why there are so few LoRAs like this floating around. Even a 5090 didn’t have enough VRAM to train it. I had to use one of the 48 GB Ada cards. On top of that, finding usable flat panoramic 360° video datasets was a nightmare, so I couldn’t build a massive dataset. Thankfully, I didn’t need one. I’ll be real though: if this had failed after the two days of training, I would’ve just said fuck it.
Trigger words
A 360-degree panoramic video
896 downloads · 70 likes on Civitai
SHA256
2BB6650077B0CAE497ECF87B86C2F095629F2782EA1B86BF4256142DB3162A83
Ranking badge
Updated Oct 22, 2026
360 degree panoramic shot LTX 2.3 on ModelTrends.ai: #6 Hottest Ltx2 model
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Also ranked: #6 Hottest Ltx2 LoRA
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360 degree panoramic shot LTX 2.3 Popularity Trend
Heat score since 30 Mar 2026
Heat score
8,130°
This week
n/a
Wasn't released/tracked
This month
n/a
Wasn't released/tracked
Past year
n/a
Wasn't released/tracked
360 degree panoramic shot LTX 2.3: Heat score since 30 Mar 20267,000°7,361°7,722°8,083°8,444°Mar 2026May 2026Jun 2026Jul 2026Sep 2026Oct 20268,130°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.
+892°
Civitai downloads
896 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.
+278°
Likes
70 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.
+19°
Adoption rate
About 1 downloads a day, measured between two readings of the sources, never guessed from a lifetime average. Speed weighs a quarter of the download term, so a fresh surge shows without letting a one-day spike outrank years of use.
+100°
Family boost
+100° because this is a LoRA of a family this site is nudging forward right now. It is a bounded nudge inside the score and is listed here openly; it can never hide a model or outweigh a thousandfold difference in downloads.
−159°
Age
−159° because the Ltx2 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 8,130°, 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.
    896 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.
    +892°
    7,892°
    running total
  3. 3
    Add the likes.
    70 likes and thumbs up, at half the weight of a download.
    +278°
    8,170°
    running total
  4. 4
    Add the adoption rate.
    About 1 downloads a day right now, measured between two readings, at a quarter of the weight.
    +19°
    8,189°
    running total
  5. 5
    Family boost.
    An open, bounded nudge for LoRAs of a family this site is pushing forward right now.
    +100°
    8,289°
    running total
  6. 6
    Take off the age.
    The Ltx2 weights came out in 2025: 150° a year, up to 750°, growing until then.
    −159°
    8,130°
    running total
  7. =
    The heat score.
    Where this model stands on every list of this site. Nothing else adjusts it.
    8,130°
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.
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LTX2.3_360vr.safetensors
643 MB · SafeTensor
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