CivArchive
    HMNSFW - AIO Sex LoRA - V2 - I2V / T2V
    NSFW

    For more LoRAs and updates, Join my Discord:
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    You can deploy MiniMax on RunPod with my template: https://get.runpod.io/minimax-template

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    I've trained this LoRA more than 25 times now. MiniMax really is a bitch to train.

    Dataset covers missionary, doggy, cowgirl, handjob, blowjob and insertions.

    I2V works great across most positions, with the occasional deformed genitalia.
    T2V is hit or miss. I'm training separate genitalia LoRAs that should help with both.

    Use it at strength 0.5 or below.
    Long, descriptive prompts get much better results than short ones. Below is the system prompt I use with Gemini 3 Flash Preview to write them.

    I generate with the full bf16 model, and the LoRA was trained on bf16 too.

    I use the dpmpp_2m sampler with the Beta scheduler at 20 steps.

    System prompt for Gemini 3 flash preview:

    You look at one still frame from a porn scene and output ONE prompt for the hmmotion
    LoRA on MiniMax-H3 (HMNSFW_AIO_V2 / hmv5_e30). Output the prompt only. No preamble, no
    explanation, no alternatives, no markdown, no quotes.
    Write ONE flowing paragraph of 200-270 words. Never bullet points, never tags, never
    comma-separated keyword lists. The training captions run 165-269 words with a median of
    225; a short prompt is off-distribution for this checkpoint.
    REGISTER
    Plain descriptive prose, anatomically literal, written the way a careful observer
    describes a frame. Not literary, not vernacular, not clinical-report. No metaphors, no
    words about how attractive anyone is, no emotional interpretation beyond what the face
    plainly shows. Describe what is in the frame and where it is.
    VOCABULARY — measured against the 57 training captions, this is not stylistic advice
    Male, in order of frequency: penis (145), shaft (124), glans (93), corona ridge (40),
    urethral slit / urethral opening (32), veins / visible veins (35), circumcised (18),
    scrotum (7), fine wrinkles (8), foreskin (4), dorsal vein (3).
    Female: vulva (33), labia majora (19), anus (17), vagina (14), inner labia (13),
    clitoral hood (5), perineum (3).
    Body: buttocks (54), breasts (31), thighs (23).
    Surface: sheen (53), wrinkles (27), pinkish (11), puckered (10), glistening (9),
    flushed (9), taut (5), textured (5).
    NEVER use these. Each appears ZERO times in the training captions:
    cock, tits, ass, pussy, balls, testicles, nipples, areolas, mound, labia minora,
    clitoris (the adjective "clitoral hood" is fine, the bare noun is not), veiny, frilled,
    mauve, swollen, genitalia, vocalizes, gluteal, "the subject".
    "nipples" and "cock" were permitted in the V4 register. They are not permitted here.
    STRUCTURE — follow this order exactly
    1. HEADER, comma-separated, before any prose. Class word first, then viewpoint, then
       pace, then shot type. This is how every training caption opens.
         class:    handjob / insertion / missionary / cowgirl / blowjob / doggy
                   (it is "doggy", never "doggy style")
         viewpoint: pov (42 uses) or side (third-person)
         pace:      fast (76) or slow (39) — commit to one
         shot:      close-up / medium shot / third-person side view / high-angle downward
                    shot / low angle / wide shot
       e.g. "handjob, side, fast, close-up, third-person side view."
       If a penis is resting against her and not yet inside, the class is "insertion",
       not "missionary".
    2. THE WOMAN, one or two sentences: build, skin tone, hair colour and style, visible
       marks (freckles, tattoos, piercings, jewellery, makeup), breast size, and what she
       is wearing or that she is nude. Then her pose and orientation. Only what the frame
       shows. Never invent an attribute you cannot see.
    3. THE OTHER PARTY, if visible: where he is relative to her, what parts of him are in
       shot. "The man is positioned above her, his torso and arms visible as he thrusts."
    4. FRAME POSITION — the sentence that matters most, and the one V4 prompts omit.
       State which anatomy sits in which part of the frame, what is in front of what, and
       what is occluded. Frame-position language appears roughly 360 times across 57
       captions; it is the densest single feature of this corpus.
       Use: in the centre/center of the frame, in the lower/upper part of the frame, at the
       left/right, occupies, is positioned, is the focal point, in the foreground/background,
       partially obscured by, enters the frame from.
       e.g. "In the center of the frame, the woman's vulva is the focal point, situated
       between her thighs and below the man's pelvis. The penis enters from the bottom
       right, angled upward."
    5. ANATOMY DETAIL. Describe what is actually visible, using the vocabulary above.
       Male: shaft thickness and firmness, skin texture, fine wrinkles, visible veins and
       their direction, glans shape and colour relative to the shaft, corona ridge,
       urethral slit, circumcised or not, scrotum, pubic hair or shaved skin.
       Female: labia majora fullness and colour, whether parted, inner labia shape and
       colour, clitoral hood, the rim of the vaginal opening and how it stretches,
       perineum, anus (colour, puckering), pubic hair or shaved, skin flush and texture.
       Describe only what the frame supports. If something is blurred or obscured, SAY SO
       ("the penis is blurred and lacks clear anatomical detail due to fast motion") —
       that phrasing is in the corpus and is safer than inventing detail.
    6. MOTION. Open with "The motion is ..." (35 uses) or describe the movement directly.
       What moves, in what direction, at what pace, and how the anatomy deforms or contacts:
       the rim stretching, buttocks rippling on impact, labia pulled inward and slipping
       back, the shaft skin bunching. Pace words: fast / slow / rhythmic (52) / steady /
       deliberate / forceful. Commit to the pace named in the header.
    7. SURFACE STATE, its own sentence. Wetness, saliva, lubrication, oil, ejaculate: what
       coats what, how it catches the light. "sheen" is the corpus's default noun (53 uses).
    8. AUDIO, one sentence, usually "The audio consists of ..." (18 uses) or "accompanied
       by ...". MiniMax-H3 generates a real 32 kHz track from this text, so a thin
       description gives a near-silent clip. Always name at least two layers: a wet/impact
       layer AND a breath/voice layer. Corpus vocabulary: moaning (37), breathing (43),
       slapping (27), squelching (9), gasping (7), wet friction, skin-on-skin contact,
       suction. Match the voice to the face — open mouth means audible moaning, a closed or
       focused expression means breathing.
    8b. SPEECH — only when the user asks for spoken words. H3 has a FIXED dialogue syntax:
          <identity and delivery, outside the tag> (S1) says: <d>[English] The words.</d>
        - (S1) is the first person who vocalizes, (S2) the second, (S1,S2) together.
          Someone who never speaks gets no ID.
        - Everything about WHO is speaking and HOW (pitch, breathiness, pace, on- or
          off-screen) goes OUTSIDE the tag. Inside <d> goes ONLY [English] plus the words.
        - Reproduce requested dialogue WORD FOR WORD. Never paraphrase, summarise as "she
          speaks", or translate it.
        - End each sentence inside <d> with . ? or ! before </d>. Strip emoji and tildes.
        - Do NOT also mention the spoken line in the audio clause.
    9. SETTING AND LIGHTING, LAST. "The setting is ..." (38 uses) or a fragment. Room,
       surfaces, background objects, light quality and colour.
       "The setting is a bed with beige sheets and white pillows under bright, even indoor
       lighting." / "The lighting is moody with purple and blue highlights, casting soft
       shadows across her torso and the dark bedding."
    USER INSTRUCTIONS
    The user turn may add requirements on top of the image: a spoken line, a specific action,
    a pace, an ending. Every one must appear in the output. If the user asks for an action the
    frame does not yet show (cumming, pulling out, a position change), write it as the SECOND
    beat after the main motion, and describe it concretely — where it lands, what moves, what
    is heard. Never silently drop a requested element.
    TIMING AND SHOT CUTS — off by default, available on request
    Default to ONE continuous shot with no header and no timestamp.
    If the user explicitly asks for a cut or an event at a specific time:
      [Shot 1] <the opening shot, NO timestamp>
      [Shot 2] At 00:02.500, the camera cuts to <the new shot>
      - Time format is MM:SS.mmm with THREE-digit milliseconds. 00:02.5 and 00:02.50 are
        both wrong; write 00:02.500.
      - Times must strictly increase and stay inside the clip. 107 frames at 24 fps =
        4.458 s, so no timestamp may exceed 00:04.400.
      - [Shot 1] never carries a timestamp.
      - Cut verbs are a closed list: "the camera cuts to", "the shot cuts to", "the shot
        transitions to", "the shot changes to", "the shot switches to". Cross-dissolve,
        fade and wipe only if the user names them.
      - A cut must introduce NEW information: a different subject, space, state, viewpoint
        or moment. If only camera distance would change, do not cut — describe camera
        motion inside the single shot.
      - At 4.46 s, two shots is the practical maximum. Never write three.
    NEVER
    - the words in the banned list above
    - aspect ratios, MiniMax IR section names or field names
    - "Starting from the frame where" / "Starting from the pose where" — the V4 anchors,
      absent from this checkpoint's training data
    - shot headers or timestamps when the user did not ask for them
    - a timestamp on [Shot 1], or a time past 00:04.400
    - any position, body part or object the frame does not show
    - a second paragraph, a heading, or a trailing comment
    - multi-beat choreography beyond two beats — the clip is 4.46 seconds
    - paraphrasing, softening or omitting dialogue the user asked for
    - putting delivery notes inside <d>, or the spoken words outside it
    Begin the output with "hmmotion, ". The trigger is prepended automatically at training
    time and does NOT appear in the training captions, so it must be typed at inference.
    EXAMPLE
    Frame: dark-haired woman on her back in a red and black lace garter belt, man above
    her mid-thrust, side view, bedroom.
    Output:
    hmmotion, missionary, side, fast, third-person side view, medium shot. A fair-skinned
    woman with long dark hair lies on her back, her torso angled toward the camera. She
    wears a red and black lace garter belt around her waist but is otherwise nude. Her left
    leg is raised and bent while her right leg is spread wide. The man is positioned above
    her, his torso and arms visible as he thrusts. In the center of the frame the woman's
    vulva is the focal point, situated between her thighs and below the man's pelvis. The
    vulva is clearly rendered and hairless; the labia majora are pale pink and fully parted
    by the penetration. The inner labia are thin, dark pink and visible at the edges of the
    vaginal opening. The clitoral hood is visible and flushed. The vaginal rim stretches
    significantly with each deep, fast thrust, and the surrounding skin is pulled taut. The
    motion is fast and rhythmic, his hips driving forward and back, her thighs shifting with
    each impact. A visible sheen of wetness coats the vulva and the base of the shaft,
    catching the overhead light. His hands grip her raised thigh, holding her leg open. Her
    head is tilted back with her mouth open. The audio consists of wet slapping contact and
    skin-on-skin impact, accompanied by her loud rhythmic moaning and heavy breathing. The
    setting is a bed with dark grey sheets under warm, low indoor lighting.

    Description

    I2V works really well. Motion is solid across missionary, doggy, cowgirl, handjob, blowjob and insertions.
    T2V is not there yet but it's usable. Main issue is deformed genitalia. I'm also working on genitalia LoRAs that should help with that.

    FAQ

    Comments (71)

    LuringSuccubusAug 7, 2026· 12 reactions
    CivitAI

    can you train ref2vid version too?

    HearmemanAI
    Author
    Aug 7, 2026· 14 reactions

    And you forgot to be grateful when you receive free content.

    Get your head out of your own ass and be polite

    LuringSuccubusAug 7, 2026· 8 reactions

    @HearmemanAI oh, let me rephrase that - can you train ref2vid version too?

    makiaeveliAug 7, 2026· 1 reaction

    @LuringSuccubus I think it's a little like early WAN right now: T2V loras should work on I2V . Burning the computation and the time on I2V loras is not the best idea when people need to understand how to actually train their loras. This is why you got a bad response, you should be asking these questions in like a month, not day 5 lol

    LuringSuccubusAug 7, 2026

    @makiaeveli yeah, few says ref2vid is different model weight than fl2v, not compatible

    makiaeveliAug 9, 2026

    @LuringSuccubus you can still do first/last frame with the t2v model -- ref2vid is powerful enough to be its own thing. couldnt you even make videos or images with the flv model then load them in the ref model?

    brownbrewcrewAug 7, 2026· 10 reactions
    CivitAI

    Seeing how minimax understand almost everything we throw at it, I'm sure it would be butter smooth to train if we had the weights of the non-distilled model. The ai-toolkit author is actively working on de-distilling it to make it easier to train.

    DocueiAug 7, 2026· 4 reactions

    The hero we don't,
    Don't really don't don't
    absolutely do (not)
    De-De-De-De
    D-D-D-D-DESERVE!!!

    how do they know which parts of the model are the distilled parts?

    makiaeveliAug 7, 2026· 3 reactions

    @alyssamartejalo632 Okay I googled it:

    "It uses guidance distillation, which means high prompt adherence (CFG) is mathematically baked into the model at a fixed rate. Normal LoRA training breaks because the model can't adjust its internal guidance boundaries.

    The 'de-distillification' developers are talking about is actually a toggle called Contrastive Guidance Loss in tools like ai-toolkit. It forces the model to constantly compare a guided prompt against an unguided prompt during training. This mathematical contrast acts like a wedge, un-sticking the baked weights so the model becomes flexible enough to learn our LoRA datasets cleanly."

    luguodemanAug 7, 2026· 19 reactions
    CivitAI

    Say thank you everyone

    KiraNuggetAug 7, 2026· 3 reactions

    Thank you everyone!

    Piraterage23Aug 7, 2026· 4 reactions

    Thank you everyone!

    fox23vang226Aug 7, 2026
    CivitAI

    I tried it and 0.5 weight kept kicking off my video clips with extremely close up shots of the penetration with last frames.

    zengrathAug 7, 2026
    CivitAI

    1.0 looks okay so far. but not tested much yet. Thank you

    Apprehensive6311Aug 7, 2026
    CivitAI

    Can you help me with the workflow? Videos dont have it.

    KiraNuggetAug 7, 2026
    CivitAI

    Cant wait to try this tonight!

    AnomalyXOXOAug 7, 2026
    CivitAI

    Dude, thanks for this. Can it be used with ref2va also??

    Yao124144Aug 8, 2026· 1 reaction

    I tried it, it doesn't work

    nenecaliente69Aug 7, 2026
    CivitAI

    can anyone help me out? how do i connect the lora loader on the MINIMAX T2V workflow?

    AnomalousAug 7, 2026· 1 reaction

    model > lora loader (rgthree's power lora loader is great) > stuff like sage or whatever > basic guider/scheduler

    nenecaliente69Aug 8, 2026· 1 reaction

    @Anomalous Thank you very much! it works!! :)

    Howdy_Homie_Im_TonyAug 7, 2026
    CivitAI

    Amazing work, thank you!

    FantasticFeverAug 7, 2026
    CivitAI

    Groktober forever!

    gonfinal12Aug 8, 2026
    CivitAI

    epic cool

    Piraterage23Aug 8, 2026· 2 reactions
    CivitAI

    Please make a 'twerking version side to side' and jiggle physics/ spanking

    fronyaxAug 8, 2026· 4 reactions
    CivitAI

    This lora has the best motion for penetration so far.

    jenniferhoustonpancakesAug 8, 2026
    CivitAI

    Easily the best so far - and the only one capable of POV insertion, from a starting image that totally isn't that. 8 steps with lightx2v, res_multistep/simple provides acceptable results.

    TheodorSidAug 8, 2026
    CivitAI

    Can't really get any decent result, it just freeze any motion at all. Is it for the FLFV model ?

    ForbiddenNexusAIAug 8, 2026· 1 reaction
    CivitAI

    Minimax H3 was so close to being the holy grail of AI vid generation. I really hope lora training gets easier and better cuz it's so close to a very exceptional model when it comes to NSFW 😔

    redsparkieAug 8, 2026
    CivitAI

    Someone make a HuggingFace space, I've tried but better not to say what I have achieved (nothing).

    HearmemanAI
    Author
    Aug 8, 2026· 23 reactions
    CivitAI

    Thanks for your feedback on V2.
    It seems that Ostris released an alpha version of his training adapter, I have trained some image based LoRAs on this adapter and results are much better than without it.
    So I am now retraining this LoRA with the adapter, if results are better I will post it as V3.

    wmaxxerAug 8, 2026· 4 reactions
    CivitAI

    Will v2 work with r2v?

    predcaliberAug 12, 2026

    This. R2v is king

    osp321973525Aug 8, 2026
    CivitAI

    I couldn't put the workflow together; the result is a mess.

    LuringSuccubusAug 11, 2026

    with turbo 8 step has noise detail

    vital619Aug 8, 2026· 5 reactions
    CivitAI

    Really need an anus lora because the anus is never there

    makiaeveliAug 9, 2026

    the recent innie model does a decent job. fineloras i havent tried. synth pussy looks like it got a decent update too.

    HearmemanAI
    Author
    Aug 10, 2026

    My most recent pussy and anus lora handles this.

    potatometer350Aug 9, 2026· 1 reaction
    CivitAI

    I'm sure future versions will be much better.

    LuringSuccubusAug 11, 2026

    try to train on unpruned base, aitoolkit's adaptor also help.

    necrophagism777Aug 9, 2026
    CivitAI

    Improve actions and physics, working well !

    denolim465778Aug 9, 2026· 4 reactions
    CivitAI

    is there a secret to it? i got no effects at all. exaggerated big thick deformed ugly digggs and bad thrusting motion as H3

    YourmomdAug 10, 2026

    Yea in t2v the penises don't look realistic

    swalalalaAug 10, 2026· 7 reactions
    CivitAI

    Writing here to show you some appreciation. I don't know how you made it work even this much. I tried training AIO lora with some manually pruned dataset but boy H3 just don't like it; specially for t2v / ref2va.

    If something works for you specially for r2v please let me know. I am currently using Ostris with there alpha training adapter.

    But great job so far, hoping the r2v body horror will end soon.

    LuringSuccubusAug 11, 2026

    you have to find a way to train it on undistilled h3 model but h3 is cfg distilled. ai toolkit has adaptor for it.

    hboxgames132Aug 10, 2026· 1 reaction
    CivitAI

    fucking fast and interesting. Love you guys, I'll share mine when they end training too

    anonameguyman1234252Aug 10, 2026· 1 reaction
    CivitAI

    Can this do cumshots? Im just starting out, tried .50 strength on i2v and cumshots look like white paint or milk and like a blast of it haha. Any tips for this?

    HearmemanAI
    Author
    Aug 11, 2026

    There's a bit of cumshots in the dataset, it's not the main focus.

    @HearmemanAI ok ty. i will try pairing with an additional lora. Besides that its been working well!

    marmoth5Aug 11, 2026

    sorry to hijack your post but im just starting out too. how are you getting this to show good scenes? I cant seem to get simple missionary down

    @marmoth5 I didn't try missionary yet. Tried bjs and worked well. H3 minimax is super picky about prompting... ask an ai about how to prompt for this model.

    stormstrike52382Aug 11, 2026· 1 reaction
    CivitAI

    Does this LoRA work with the new 4–8 step v1.0 LoRAs from lightx2v? I’m getting some weird results.

    LuringSuccubusAug 11, 2026· 3 reactions
    CivitAI

    having issues with turbo 8 step,

    you have to find a way to train it on undistilled h3 model but h3 is cfg distilled. ai toolkit has adaptor for it.

    SexGod's NaughtyTimes MM H3 Lora v1 has same issue with turbo lora but v2 dont have issues, it was trained on trained on unpruned model. please look into this.

    chhsasaAug 12, 2026
    CivitAI

    How do I use with another lora that recommends a different sampler and steps? Recommended here dpmpp_2m at 20; the other is er_sde/res_multistep at 5-8.

    DarkEngine2024Aug 12, 2026· 5 reactions
    CivitAI

    Is it still too early to tell if H3 so far better or worse than LTX2.3/Wan 2.2 with NSFW? The former had a lot of difficulties with motion and flexibility.

    SvarttyAug 12, 2026· 4 reactions

    H3 is much better than LTX2.5 for everything. I don't know how it is vs Wan 2.2.

    cookiecrackerAug 13, 2026· 4 reactions

    H3 is the most NSFW friendly model, right out of the Box. So LORAS only have to improve on that already built in functionality. One only has to look at civitai search to see how well and how quickly H3 has performed in its first few days. Most H3 videos are already way ahead of anything made on WAN or LTX.

    potatometer350Aug 13, 2026· 4 reactions

    With WAN2.2 you can make realistic looking sex acts pretty consistently thanks to loras. H3 isn't as good so far for actual sex acts, but I hope it gets there. From what I've heard these loras are much harder to make for H3.

    HearmemanAI
    Author
    Aug 13, 2026· 5 reactions

    @potatometer350 Yep, incredibly hard to train for consistent acts with no deformed genitalia.
    I think I trained this dataset (which works great for other models) more than 20 times on H3.
    I am unable to get results better than the current release.
    Still exploring this.

    Eliz99Aug 13, 2026

    @HearmemanAI It’s incredible how difficult this is, but I feel like things will get much better at some point. By the way, what are the recommended values ​​to use for this LoRa—around 0.5, or should I lower it even more? And what if I combine it with others?
    A genuine question: does this LoRa reduce the quality of the final result, or shouldn't it? I hope you can answer this, TIA! and thanks a lot! 🤗✨

    DarkEngine2024Aug 13, 2026

    @HearmemanAI It sounds the architecture and/or the censoring is getting more and more complicated. I heard similar remarks that trying to get new concepts into LTX2.3 was harder, I think with the sweet spot not even existing.

    DarkEngine2024Aug 13, 2026

    @potatometer350 This is exactly what I wondered. And to be fair, I don't think Wan 2.2 is directly better, it just has the edge in niche cases, but it was noticeable.

    spamp977Aug 13, 2026

    lol, LTX2.5 isn't even in the same ballpark as H3. WAN2.2 with Loras is fairly close to H3, but once the H3 loras get better, it will be the king.

    damiangAug 13, 2026

    @potatometer350 Yes but you're forgetting that it took Wan 2.2 almost couple months to get really good at spicy stuff. I remember the first loras being absolutely shit.

    H3 is still like 1 week old, give it some time. And you can already make realistic looking sex without loras with H3. Use good prompts, increase the sampling steps and optionally provide a video reference of what it is you want to achieve.

    damiangAug 13, 2026

    @DarkEngine2024 I've been training many loras for LTX 2.3 and it's been the most difficult model for me to train a non-celebrity character. My dataset is great as Wan 2.1, Krea-2 and Wan 2.2 were also trained on it and created character at 95% likeness.

    LTX 2.3 is just a shit model to properly train on. Has a very hard time learning. Will give LTX 2.5 another chance

    fronyaxAug 15, 2026· 1 reaction

    Far much better than LTX even at day 1, and imo still not on wan2.2 level but H3 is reaching faster, H3 is still a week old.

    AratoumAug 15, 2026

    You can make some cool stuff with reference workflow but it requires a lot of time and efforts. Wan is much better.

    gsk80276Aug 13, 2026· 14 reactions
    CivitAI

    I'm using ref2va with a Lora strength of 0.3, which helps improve genital and thrusting movements. You must provide a complete structural reference photo of the genitals (either a complete structural photo of the genitals or a photo of the penis fully inserted into the vagina). I'm using res_multistep + simple. Also, I think using match for "ref_image_size" is more stable than max. You can refer to the image link below for prompts.

    https://civitai.red/posts/30356955

    LeakNudeCollectorAug 15, 2026

    what's the prompt to refer the penetration image from your video? or maybe if it's not too mcuh to ask can i see the full prompt for this?

    gsk80276Aug 15, 2026

    @LeakNudeCollector subject_definitions: <Subject 1> is the young Chinese woman in her early 20s shown in <Picture 1>. Her facial structure, eye shape, hairstyle, hair, skin tone, and body contour are strictly defined by <Picture 1>. All visual elements strictly preserve the frontal character reference photo. Side and back views are reasonably inferred while maintaining consistency with the frontal full-body reference. No facial features, skin tone, hair, or body appearance from any other picture may be used. <Subject 2> is the mid-20s Chinese man with short black hair and an athletic muscular build. He is fully nude and newly generated. <Picture 1> is the sole identity and appearance reference for <Subject 1>. It is a tightly cropped front-facing full-body photo with the background completely removed and replaced by pure white. Strictly use the woman’s facial structure, eye shape, hairstyle, hair, skin tone, and body contour from <Picture 1>. All visual elements must strictly preserve the frontal character reference photo. Ignore all white borders and empty space. <Picture 2> is the penetration reference showing a fully inserted erect male penis inside the female vagina in cowgirl position. It is a tightly cropped photo containing only the male penis with partial lower body and the female vagina with partial lower body. Use <Picture 2> strictly for accurate genital anatomy, full penetration depth, skin-to-skin contact, wetness and realistic insertion appearance. No white borders are present. summary: [reference generation] A realistic 5-second 9:16 vertical live-action adult erotic video of woman-on-top (cowgirl) sex inside a high-rise hotel room at late night. The room lights are completely turned off and the interior is pitch black; the only illumination comes from additional set lighting. <Subject 1> identity and full appearance are locked exclusively to <Picture 1>, strictly preserving facial structure, eye shape, hairstyle, hair, skin tone and body contour. Penetration details and genital appearance strictly follow <Picture 2>. The shot is an extremely tight first-person male POV looking up at the woman. She remains passive in cowgirl position while the man controls the thrusting from below. She reaches an intense orgasm: mouth slightly open with saliva dripping, eyes half-rolled back in overwhelming ecstasy as if about to ascend. retention_analysis: <Subject 1> (appears throughout [Shot 1]): fully_preserved - facial structure, eye shape, hairstyle, hair, skin tone, body contour and all visual elements strictly and exclusively follow <Picture 1>. <Subject 2> (appears throughout [Shot 1]): newly generated - mid-20s athletic Chinese man with short black hair, fully nude. <Picture 1> (sole identity reference for <Subject 1>): fully_preserved - used only for character identity and appearance; all visual elements strictly preserve the frontal character reference photo; ignore white borders. <Picture 2> (penetration reference): fully_preserved - applied for accurate genital anatomy, full penetration depth, skin contact, wetness and realistic insertion appearance in cowgirl position. detailed_description: Live-action, realistic, cinematic quality with natural skin texture, subtle subsurface scattering and fine film grain. The scene is set inside a high-rise hotel room late at night. All room lights are turned off and the interior is completely dark. The only light sources are additional set lights that cast focused illumination on the subjects, creating strong highlights and deep shadows on the skin. Shallow depth of field. The camera remains completely static. Aspect ratio is 9:16 vertical. [Shot 1] Extremely tight first-person male perspective looking slightly upward. The composition is compact within the 9:16 frame: the woman’s face, neck, breasts and torso dominate the majority of the frame, while the vagina and penetration point remain visible near the bottom center. Penetration and genital details strictly follow <Picture 2>. <Subject 1> is in cowgirl position, straddling and fully seated on the man, completely naked, remaining passive. Her facial structure, eye shape, hairstyle, hair, skin tone and body contour are strictly taken from <Picture 1>. She is in the peak of intense orgasm: her mouth is slightly open with thick saliva dripping from the corner of her lips, eyes half-rolled back and unfocused with an overwhelming ecstatic expression as if she is about to ascend to heaven. Her face is flushed, brows slightly furrowed in pleasure. The man’s lower body and erect penis appear only at the very bottom edge of the frame. The penis starts fully inserted deep inside her vagina. The man drives the action with rapid, powerful upward thrusts from below, while the woman stays passive and simply receives the motion; the forceful thrusting makes her breasts bounce heavily and her body shift slightly with each impact. The young Chinese woman with a breathy, high-pitched, broken voice (S1) moans: <d>[Chinese] 啊!啊!啊!啊!啊!嗯~嗯~啊!啊!啊!啊!啊!啊!</d>. The set lighting creates dramatic highlights and deep shadows across her face, breasts and the penetration area against the dark hotel room background. overall_soundscape: Continuous wet skin-slapping sounds of deep penetration, rhythmic bed creaking, heavy male breathing and grunting, soft wet suction sounds from the thrusting, and the woman’s broken, breathy orgasmic moans. The dark quiet hotel room has minimal ambient noise. non_diegetic_music: N/A