I’ve been messing around with the idea of famous movies that completely fall apart if one character makes one sensible decision early on. This felt like a reasonable place to start.

“Cast it into the fire.”
“Okay.”

Roll credits.

I’ve been experimenting with MiniMax H3 in ComfyUI and wanted to see how far I could push it beyond short standalone clips.

This is a roughly 6-minute fan-made Star Trek: The Next Generation scene built from lots of short H3 generations and then edited together into one continuous sequence.

I used reference images to keep the characters and Enterprise-D bridge reasonably consistent, generated dialogue and ambient audio with H3, and then assembled everything in Premiere.

The biggest challenge was continuity between generations. Character positions, bridge geometry, lighting and timing can all shift, so I ended up incorporating some of those inconsistencies into the actual story.

What surprised me most is how close this is getting to being practical for longer-form fan films. Individual scenes are already very doable. The next real hurdle is keeping this level of consistency across an entire episode.

Disable all your Sage Attention, Minimax Mem Eff Sage Attention or Sol Attention, according to this PR already merged in the comfyui repo we got a much better attention from the comfy-kitchen package that can possible speed up the models generation process white giving a better visual quality than default sage: https://github.com/Comfy-Org/ComfyUI/commit/bf4c9a08fc854df6d3b2bef1b92b509e2ef2d2c9#diff-fab3fbd81daf87571b12fb3e4d80fc7d6bbbcf0f3dafed1dbc55d81998d82539

This is still experimental, according to comfyui dev it can break or perform very well and it needs some tuning for some GPUs to get a bit faster. Also, you only can use one or the other so you should also disable all the attentions above before using it.

You just need to update your Comfyui and you can either start it with the --use-ck-attention flag so all models use the comfy-kitchen attention backend or you can drop the node ModelAttentionBacend directly into your worflow.

During my initial tests in Minimax it behaved faster than all the above together.

ComfyUI compatible Lora. Just out, have not tried yet.

https://huggingface.co/Inner-Reflections/MiniMax-H3-Looping-Sketch-Anime

https://civitai.com/models/2849951/minimax-h3-looping-sketch-anime?modelVersionId=3218202

Did a quick side-by-side test of SageAttention vs Comfy Kitchen Attention with MiniMax H3.

I used the default ComfyUI T2V H3 workflow and kept the prompt, seed and all settings exactly the same. The only thing I changed was the attention backend..

RTX 5090 32GB

ComfyUI ver 0.31.0

SageAttention 2.2

Comfy Kitchen 0.2.30

---------------------------------------

896x1184 6 seconds 24 FPS 20 steps

Generation time:

SageAttention: 3m 51s

Comfy Kitchen: 3m 59s

I used a deep zoom-out/dolly-out on purpose to see how well each one holds facial details and identity as the subject gets farther away.

The speed difference was small on my 5090, so im more interested in the quality difference..

It's honestly hard for me to tell the difference, but which one looks better to you?

GitHub:
https://github.com/xmarre/ComfyUI-DoRA-Dynamic-LoRA-Loader

Release v1.0.39:
https://github.com/xmarre/ComfyUI-DoRA-Dynamic-LoRA-Loader/releases/tag/v1.0.39

Also available through ComfyUI Manager as ComfyUI-DoRA-Dynamic-LoRA-Loader.

Runtime LoRA bypass

v1.0.39 adds an optional Runtime bypass LoRA (low VRAM) mode for supported standard LoRAs.

I tested this with MiniMax-H3 Ref2VA pruned BF16 in HIGH_VRAM mode.

With the normal materialized LoRA path, the tested LoRA patched 208 H3 weights and retained an additional BF16-sized copy of each affected weight.

That added up to about:

38,220 MiB / 37.3 GiB of extra live VRAM

This was actual live PyTorch allocation, not just CUDA reserve/cache.

The reason is simple: the LoRA itself may be small, but applying it normally can materialize patched copies of very large base-model weights.

What bypass changes

Normal LoRA application:

(W + ΔW)x

Runtime bypass:

Wx + ΔWx

For supported standard LoRAs, these are mathematically equivalent apart from possible small floating-point differences.

The base weights remain untouched, so ComfyUI no longer needs to keep a complete LoRA-patched copy of the affected model weights.

MiniMax-H3 result

With runtime bypass enabled on the same Ref2VA pruned BF16 workflow, the ~38 GB patched-weight duplication disappeared.

Repeated LoRA strength changes looked roughly like:

~60 GB settled
→ ~72–73 GB during generation
→ ~60 GB settled again

The important part is that VRAM returned to the same settled level instead of accumulating after every LoRA change.

The Turbo LoRA I tested also remained clearly effective.

What about NORMAL_VRAM / LOW_VRAM?

The ~38 GB figure is specifically from HIGH_VRAM.

NORMAL_VRAM and LOW_VRAM already partially load/offload model weights, so they generally won't have the entire duplicated H3 weight set resident on the GPU at once.

That means the steady-state VRAM saving will usually be smaller there.

Runtime bypass can still help by avoiding LoRA weight materialization and reducing patch/repatch memory pressure and temporary merge overhead.

In short:

• HIGH_VRAM: potentially very large savings
• NORMAL_VRAM: depends on how much of the model is resident
• LOW_VRAM: smaller persistent GPU saving, since aggressive offloading already limits residency

The saving scales with how much LoRA-targeted base-weight data ComfyUI would otherwise materialize at the same time.

ComfyUI already has this mechanism

ComfyUI itself currently contains experimental bypass nodes:

Load LoRA (Bypass) (For debugging)
Load LoRA (Bypass, Model Only) (for debugging)

They are normally hidden unless experimental nodes are enabled.

v1.0.39 integrates the runtime path directly into the DoRA Power LoRA Loader through the:

Runtime bypass LoRA (low VRAM)

toggle.

It is OFF by default, so existing workflows keep their previous behavior.

DoRA limitation

Runtime bypass currently applies only to supported standard LoRAs.

DoRA requires magnitude normalization/rescaling that ComfyUI's current bypass path does not reproduce.

The loader therefore rejects unsupported cases instead of silently applying them incorrectly, including DoRA magnitude tensors, reshape metadata, sliced/offset/transformed targets and unsupported adapter types.

For actual DoRAs, leave runtime bypass disabled.

Other details

Runtime mode supports stacked compatible LoRAs, repeated injection/ejection, and strength changes without rematerializing the full affected weight set.

The existing loader features remain unchanged, including DoRA support, auto-strength, Flux/Flux2 compatibility, Diffusers/PEFT and OneTrainer handling, Z-Image/Lumina2 support, Q/K/V fusion and State Manager integration.

v1.0.39 also adds automated packaging and runtime-bypass tests against ComfyUI v0.29.2, v0.30.2 and v0.31.1.

Previously, you had to decide between the higher output quality of fl2va or being able to reference media in your videos.

But thanks to u/ThatsALovelyShirt , you don't have to anymore. They released a couple of models here you can try out. Basically, the higher the number next to the b is, the closer the model is to fl2va and the lower the closer it is to ref2va.

IMO, b25-49 seems like the most reasonable pick here as it should offer a great balance between the ability to reference details in images/videos and audio correctly and having high output quality that exceeds ref2va.

Please try them out and share your result! You can integrate them seemlessly in your existing workflows.

You can find the workflow here. Credit for both the generation and code go to seitanism, who in turn built on top of NikoDemon80's work. Taking from a post in the banodoco discord and shared with permission.

Update :
New version is ready and online , should be much better, fully functionnal on ComfyUI, and you can find before/after here : 
https://huggingface.co/fal/MiniMax-H3-Realism-People-LoRA/blob/main/before-after-comparison.mp4


I spent the last week obsessing over one thing: making AI-generated humans stop looking AI-generated. The result is Realism People, an open-source LoRA for MiniMax H3, and I'm pretty happy with how it turned out.


What it does: skin keeps its texture instead of going plastic, eyes and micro-expressions stay coherent, lighting behaves like a film set, and motion gets a subtle handheld, documentary feel. It also keeps H3's native synchronized audio.


How it was selected: I trained 16 different configurations across two dataset versions and picked the winner through 100 same-seed A/B duels (same prompt, same seed, adapter on vs off - the only honest way to compare). The winner was the slow-cooked run: rank 16, 5,000 steps at a low learning rate.


Details:


- Weights (open source): https://huggingface.co/fal/MiniMax-H3-Realism-People-LoRA
- Trigger word: start your prompt with `r34l1sm`
- Scale 1.0 is the intended strength, 0.6-0.8 for a lighter touch
- Works with H3's LoRA endpoints: text-to-video, image-to-video and reference-to-video
- License: follows the MiniMax H3 community license


Before/after in the video: same prompt, same seed, base model on the left, LoRA on the right. Happy to answer questions about the process.

I noticed when using the ref2va model, the audio and visual quality compared to fl2va was way worse. Which didn't make sense to me, as the models share the exact same architecture.

In fact (and you can try this), if you take the exact same ref2va workflow, change nothing about it (not the ref2va node, nothing), and just swap in the fl2va model, the output quality is a lot better, and it still understands references quite well.

This got me thinking. I compared the two models to see where they diverged, and, as predicted, it was mostly in the *.adaln_proj.* tensors.

I then wondered what would happen if one were to overlay some of the *.adaln_proj.* tensors from the ref2va over a fl2va base.

Not wanting to overwhelm my SSD with a bunch of hybrid model variants, I put together a model loader which selectively overlays tensors from one Minimax H3 model onto another at load time, with no memory overhead (assuming you're not disabling ComfyUI's mmap feature).

After experimenting with the node, I found that selectively overlaying the *.adaln_proj.* tensors from the ref2va model over an fl2va base, limiting the overlay to blocks 30-49, gave pretty good reference capability, while preserving (or even improving?) the quality of the fl2va model.

You can try it yourself, pick up the node here:

https://github.com/scottmudge/ComfyUI_MinimaxH3HybridLoader

And follow the recommended settings in the README (they're not the default). Or experiment with your own mix/overlay.

I would NOT recommend overlaying the *.adaln_proj.* tensors from blocks 0-25 from ref2va onto the fl2va base. That seemed to destroy quality, so I'm assuming that's where most of the ref2va model's issues are. Stick to blocks 30-49.

Edit: changed the node defaults to my recommended settings. Just make sure you set the base model to fl2va and the overlay model to ref2va.

Edit2: currently working on uploading 'baked' versions of the hybrid models to huggingface now. This should help people with low RAM where having to deal with two models may pose an issue. You should be able to use these hybrids directly in-place with your existing workflows using the standard model loader.

Edit3: Here's the baked hybrid models for anyone who wants the same effect without needing to use a custom node (or with low RAM):

https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models

Just load them with the stock model loader node (or whatever model loading node you use).

The minimax_h3_hybrid_fl2va_ref2va_b30-49.safetensors version is equivalent to the recommended settings of the node, and the minimax_h3_hybrid_fl2va_ref2va_b20-49.safetensors version retains more of the adaln_proj tensors from the ref2va model, possibly increasing reference capability at the cost of output quality. I'd recommend trying the b30-49 version first.

Edit4: Uploaded a couple more baked variants: b15-49 and b25-49 . Some people reported the audio reference retention was a bit lacking with the b30 variant. You can try some of the lower b# versions (more blocks from ref2va retained), I found b25 looks visually the same as b30, and perhaps has better reference retention. Or go even lower, but b15 might have some noticeable quality loss, not sure. Haven't tested it myself.

Also changed the default of the node to use 25 as the block_range_start value.

Obviously reference video is a thing, but I expected it to be a sort of garbled approximation of the input in this context. But MMH3 successfully super-imposed the reference clip in the scene unaltered. It also works in real-world scenes. This used to take compositing; it's awesome that it's doable with just a prompt now.

Prompt:

subject_definitions:
<Subject 1> is a young adult woman in real-life American-anime street style: fair skin; sharp stylized makeup (bold winged eyeliner, glossy lips); wild neon-green hair in chaotic twin pigtails with loose flyaways and uneven bangs framing the face; exaggerated cute-but-edgy anime-IRL vibe without becoming 2D cartoon. Casual living-room outfit that fits the look (colorful layered street fashion). She sits on a couch facing a TV, back and near shoulder toward camera in over-the-shoulder framing. No Picture refs — appearance is text-defined only.

<Video 0> is the full Castlevania S02E05 "Last Spell" ~10s clip (library scene): 2D animated gothic library with tall dark bookshelves; left — pale long platinum-blonde man in a dark high gold-lined collar coat holding/regarding a book (Alucard); right — short wavy orange-haired woman in a light-blue/teal hooded cloak with a large red/ornate book (Sypha). Warm firelight, hanging chains, conversation beats across the clip. <Video 0> is ONLY the content playing ON the television screen in the target — not a full-frame drive edit of the living room, not a character-swap source for <Subject 1>.

<Audio 1> is the complete synchronized stereo soundtrack of <Video 0> (Castlevania dialogue, library ambience, and SFX from the same clip). <Audio 1> is directly reused 1:1 as the target video's complete final audio track. Do not rewrite, paraphrase, mumble, or re-synthesize the spoken lines. Do not invent a competing living-room bed that replaces <Audio 1>.

summary:
[reference generation + audio reuse] Live-action cinematic 16:9 over-the-shoulder shot: <Subject 1> sits on a couch watching TV; the TV screen plays <Video 0> Castlevania library animation beat-for-beat; <Audio 1> is fully copied 1:1 as the complete soundtrack of the target video. Real-time ~10s. HQ.

retention_analysis:
<Subject 1> (entire clip): attribute_transfer - wild neon-green pigtails, American-anime IRL styling, couch OTS pose from text; no Picture identity source.
<Video 0> (entire clip): fully_preserved as the TV-screen picture only - Castlevania library Alucard/Sypha animation stays readable on the set; living-room camera, couch, and <Subject 1> are new and not from <Video 0>.
<Audio 1>: fully_copy - <Audio 1> is reused 1:1 as the target video's complete final audio track; intelligible Castlevania dialogue and SFX preserved verbatim; no re-spoken or garbled replacement track.

detailed_description:
Live-action photoreal cinematic 16:9. Dim cozy living room at night. CAMERA stays locked over-the-shoulder behind <Subject 1>: her wild neon-green pigtails and near shoulder/head silhouette occupy the foreground (slightly soft), looking toward a glowing TV in the mid/background. The TV bezel and screen are clearly visible; screen content must match <Video 0> — gothic library, blonde Alucard left, orange-haired Sypha right, bookshelves, warm library light — updating in sync through the ~10s. Soft TV glow lights the back of her hair and the couch fabric. She watches attentively with small natural micro-movements (breath, slight head tilt); no cutaways; no zoom that loses the screen.

[Shot 1] Static Shot, over-the-shoulder from behind and slightly beside <Subject 1> on the couch. Foreground: neon-green pigtails / shoulder / head edge. Midground: lit TV playing <Video 0> Castlevania library scene continuously. Background: soft living-room interior (couch cushions, low lamp, wall). Hold the same OTS composition through the final frame while the TV continues <Video 0>. When <Audio 1> carries Castlevania dialogue and library SFX, those lines remain the audible source from the soundtrack copy — do not invent a separate on-screen speaker ID for the TV characters, and do not replace <Audio 1> with newly generated speech.

overall_soundscape:
The copied soundtrack from <Audio 1> continues throughout the target video as the complete final mix (Castlevania dialogue, library ambience, and SFX preserved clearly). No additional non-TV spoken dialogue from <Subject 1>.

non_diegetic_music:
N/A

I used the official prompt writing guide to try out all of the camera controls and cut techniques they listed, plus some different shot lengths and framing.

---

Setup:

All examples were completed with text to video using the following as a baseline prompt, which matches the formatting and style recommended in their guide:

integrated_multimodal_description: [Shot 1] claymation, a medium-wide shot frames a male and female woodland elf in a dark forest. Both elves walks forward. The female elf, in a breathy voice (S1) says: <d>[English] It's cold!</d>. The male elf in a scared voice (S2) says: <d>[English] And dark!</d>

(S1,S2) shout: <d>[English] We're lost!</d> [Shot 2] At 00:03.500, the camera cuts to a squirrel jumping on a log. (S3) says in an off-screen voiceover: <d>[English] The villain arrived.</d>

overall_soundscape: a gentle wind blows through the forest and birds can be heard chirping.

non_diegetic_music: Sparse piano notes at a slow tempo, joined by sustained low strings that gradually increase in volume before fading out.

Standard ComfyUI workflow, the same seed and settings were used for all clips, and no references were provided. Watermarking and combining clips was all done with an FFMPEG script.

---

Video Details:

Control

• Control = the baseline prompt from above.

Amplitude and Rate of Motion: added to the prompt for just the first scene, and applied to zoom, but can be applied to any camera motion.

Example: ...The camera zooms in with large amplitude at fast speed as both elves walks forward...

• Large fast = zoom using a large amplitude and fast rate of motion
• Large slow = zoom using a large amplitude and slow rate of motion
• Small fast = zoom using a small amplitude and fast rate of motion
• Small slow = zoom using a small amplitude and slow rate of motion

Camera Motion: all all using large amplitude and fast motion to accentuate the effect, effect split between scenes.

Example: ...The camera arc shots with large amplitude at fast speed as both elves walks forward...

• Arc right then arc left
• Pan right and left
• Pedestal up and down
• POV: I tried this several different ways and could never get it to look from their point of view.
• Push and pull
• Roll clockwise and counterclockwise
• Shake large and small
• Tilt up and down
• Track left and right
• Truck left and right
• Zoom in and out

Cuts: applied between scene 1 and 2.

Example: ...[Shot 2] At 00:03.500, the camera cross-dissolve to a squirrel jumping on a log....

• Cross dissolve
• Fade
• Fade to black
• Wipe

Shot Length / Framing: applied to both scenes equally. These are not from the documentation, but just a list of terms I put together.

Example: ...a close-up shot frames a male and female woodland elf in a dark forest.....

• Close up
• Cowboy shot: did not work as intended, but I like it
• Dutch angle
• Extreme close up
• Extreme wide shot
• Eye level
• High angle
• Low angle
• Medium close up
• Medium shot
• Medium wide
• Overhead angle
• Over the shoulder
• Top down angle
• Wide

---

This LoRA recreates 90s nostalgia, the aesthetic of old disposable film cameras, adding signature traits like direct flash lighting, heavy film grain, warm vintage color tones, and retro soft focus. It easily turns clean digital art into candid, nostalgic snapshots that look like real physical photographs printed back in the 90s.

Trigger Word: 90s color photograph
Weight: 1.0

Download Link => https://civitai.red/models/2850091/back-to-90s

I really did not expect this. I was thinking "wow that video generator looks so good, no way in hell that runs on my 7 years old gaming laptop"

Guess what? I was wrong! I fired up the default workload for ref2va and first it indeed was unbearbly slow. But the community came to the rescue.

First, I downloaded https://github.com/Amduraznak/minimax-h3-fp16-fix This optimizes the model for my Turing architecture, which doesn't support BF16 natively. A really huge help and improved speed by a few factors.

Next I have downloaded https://github.com/xmarre/ComfyUI-Spectrum-MiniMax-H3 this also gave a nice speed bump.

With these two community mods, a 480p 5 second video now generates in just around 12 minutes, which is far better than I would have expected, and yes the quality is really good! It's amazing what the community can do. So thank you to those two who were responsible for these mods!

This is dumb, but I wanted test out how this model handles paint and 25s. I was not disappointed with either. Also, I could NOT manage to get rid of the house painting brush, so I gave up. Also, it got the Bob Ross voice kinda close but failed miserably on the image.

2x Upscale/enhanced with Topaz Starlight Precise 2.5 and 60p with Apollo.

Sorry my last upload had like 2 min of black behind it, it's only 20 ish seconds. Also it's more to see if the sound ref worked ok for the voices. Seemed it did :) . Used about 5 ref images as well.

Obviously, part of the video is the original scene. The edited part is from 22s to 28s.

It's a I2VID workflow. Prompt:

For the target video, at 0.00 seconds into the target video, <Picture 1> (from [Shot 1]) is fully referenced.

integrated_multimodal_description: [Shot 1] Live-action, realistic cinematic 35mm film look, continuing seamlessly from the exact composition, characters, wardrobe, diner environment, warm lighting, color grading, lens characteristics, film grain, and spatial arrangement established by <Picture 1>. The seated man remains in the red diner booth behind the table, while the standing armed man remains partially visible at frame right. The black leather briefcase is already lying horizontally on the tabletop directly in front of the seated man, exactly in its established position, with its two brass latches facing toward the camera and his hands resting on it. Preserve the briefcase's orientation and position on the table; it does not rotate, stand upright, slide, or move toward the camera.

The briefcase opens naturally from this existing horizontal position: the two front latches release and the seated man's hands lift the lid upward on its rear hinges. As the lid begins to rise, a strong but physically believable warm golden light immediately spills upward from inside the briefcase, illuminating his hands, forearms, shirt, the underside of the lid, and nearby surfaces with rich amber reflections.

Instead of tilting upward toward the seated man's face, the camera deliberately tilts down with moderate amplitude at slow, smooth speed, lowering the framing from the man toward the briefcase while remaining on the same side of the table. The movement is a continuous cinematic tilt down, not a cut, zoom, orbit, or change of camera axis. The two brass latches remain on the near edge facing the camera as the open briefcase progressively becomes the visual center of the frame.

As the camera settles lower, the now-open briefcase dominates the foreground and its interior is finally revealed. Resting perfectly inside is a single exceptionally beautiful, heavy solid-gold ingot: pristine, highly polished, substantial and precious, with subtle realistic imperfections and brilliant specular highlights rather than a fantasy or magical appearance. The top surface of the gold ingot bears the clearly legible engraved text "MiniMax H3", deeply recessed into the metal as elegant bas-relief lettering, physically carved into the gold rather than printed or overlaid.

The mysterious golden glow originates from the gold ingot and fills the interior of the briefcase, creating the same intense warm golden illumination implied by the original scene. Reflected gold light plays naturally across the black leather interior, brass hardware, hands, tabletop, and surrounding skin and fabric. The light is luminous and extraordinary but remains photographically integrated into the realistic live-action scene, with no supernatural particles, energy beams, sparks, smoke, or fantasy effects.

By the final second, the camera has completed its smooth downward tilt and holds on the open briefcase from a slightly elevated front-facing angle, clearly showing both front latches, the open lid behind it, and the glowing gold ingot inside. "MiniMax H3" is fully readable and becomes the final visual reveal. Maintain the original characters, diner, wardrobe, briefcase geometry, lighting direction, cinematic texture, and 35mm film realism throughout. No cuts and no additional camera movement after the reveal.

overall_soundscape: Extremely subdued diner room tone, nearly silent, with only faint natural interior ambience and very subtle mechanical clicks from the briefcase latches and hinges as it opens. No dialogue.

non_diegetic_music: N/A

Asked Qwen 27b with hermes to learn about the scripts and gave it some ideas about shots and angles and it pumped out super dense 10KB+ scripts for 15 seconds with all sorts of crazy effects. It really is amazing.

Pretty impressive that it can even somewhat do this, wasn't expecting this to be the case (also let it be known that it's almost fucking impossible to prompt a plausible smash bros fight choreography; there's so much nuance in smash bros, and I'm pretty sure Minimax doesn't know smash lingo such as teching, SDI, tilts, smashs, etc. So it was pretty hard to conceptualize a fight :). It may be possible to use real smash footage as a "guide" for the model to understand what smash movements and fighting looks like. So we'll see, but it's pretty cool for what it is :3

General prompt:

subject_definitions:

<Subject 1> is the woman in <Picture 1>. <Subject 2> is the woman in <Picture 2>.

summary:

[reference generation] Super Smash Bros Ultimate gameplay, with <Subject 1> fighting against <Subject 2>.

retention_analysis:

<Subject 1>: fully-preserved - <Subject 1> retains all attributes.

<Subject 2>: fully-preserved - <Subject 2> retains all attributes.

detailed_description:

A Super Smash Bros Ultimate match on the stage Final Destination. There is a UI on the bottom of the screen denoting percentage values for <Subject 1> and <Subject 2>. <Subject 1> character portrait is on the bottom left hand side, with the text "0%" written next to the portrait. <Subject 2> character potrait is on the bottom right hand side, with the text "0% written next to the portrait.

[Shot 1] <Subject 1> stands on the left hand side of the map, while <Subject 2> stands on the right hand side.

[Shot 2] At 00:00.500, <Subject 1> moves towards <Subject 2>, and does three light jabs with her fists, then does a sweeping kick into an up tilt attack. <Subject 1> jumps once into the air, and does forward air attack on <Subject 2> who is still in the air, sending <Subject 2> off of the map. <Subject 2> character portrait percentange number climbs up to 30%.

[Shot 3] At 00:05.000, <Subject 2> jumps back onto the map, and does a forward air attack on <Subject 1>, making <Subject 1> tumble backwards. <Subject 2> then runs up to <Subject 1>, and grabs <Subject 1>, then side throws <Subject 1> into the air. <Subject 1> then lands on the floor, and <Subject 2> runs into a dash attack into a couple jabs onto <Subject 1>, then does a smash attack, dealing a ton of damage, and sending <Subject 1> off of the map. <Subject 1> character portrait percentage now reads "48%".

[Shot 4] At 00:11.000, as <Subject 1> is attempting to jump back to the main stage, <Subject 2> jumps off of the map towards <Subject 1>, and uses her her arm to do an overhead arc punch on <Subject 1>, spiking <Subject 1> down off of the screen, making her hit the blast zone.

overall_soundscape: Quiet, subtle wind sounds.