The Vidu Q4 prompt generator gives you 20 free, copy-ready video prompts for Shengshu's new flagship 4K video AI. 15-reference input, native audio, action-tuned camera controls — all structured for Q4's breakthrough capabilities.
The Vidu Q4 prompt generator on this page provides 20 free, professionally crafted prompts for Vidu Q4 Preview — the latest flagship AI video model from Shengshu Technology, launched October 7, 2026. Vidu Q4 is an image-to-video and reference-to-video model that debuted at #3 globally on the Artificial Analysis Image-to-Video leaderboard (Elo 1,179), jumping from #19 in a single release.
What sets Vidu Q4 apart: it accepts up to 15 reference images to lock characters, wardrobe, props, and environments simultaneously — the highest reference count of any top video model — while outputting native synchronized audio in every generation. Resolution tops out at 4K with 10-bit color, and the model's camera intelligence is specifically tuned for action sequences and chase scenes.
Every prompt below is structured for Q4's distinct strengths — 4K cinematic, high-reference character consistency, action choreography, voice-locked dialogue, and native audio integration. Paste directly into vidu.com, the Vidu API, or YouCam.
Q4 parses full narrative descriptions — not keyword lists. Use this structure:
Click any prompt to copy — paste into vidu.com, the Vidu API, or YouCam
Image-to-video: a figure in a dark coat sprints down a rain-slicked alleyway at night — camera chases from behind at shoulder height, keeping pace through a sharp left turn, over a low obstacle, and along a neon-lit corridor of steam vents. The camera work should feel visceral and reactive: slight shake on landing, smooth acceleration through the turn. 14 seconds, 4K. Native audio: footsteps on wet asphalt, rain, distant sirens.
Image-to-video: a snow leopard stands on a high mountain ridge at dawn — wind ruffles the thick spotted coat as the cat surveys the valley below. After 6 seconds, it lowers into a crouch and springs off frame left. Static telephoto camera, deep depth of field, snow bokeh in foreground. 14 seconds, 4K, BBC Planet Earth quality. Native audio: high-altitude wind, silence on the spring.
Image-to-video using 15 reference images of a model and wardrobe: the model walks a sun-drenched Parisian colonnade — stone arches framing each step, dappled light across a white linen dress. 5 seconds of approach, a half-turn at mid-frame, 5 seconds walking away. Reference images lock character face, dress, and posture. Camera: low tracking shot transitioning to static wide. 12 seconds, 4K, Vogue editorial quality. Native audio: heels on stone, ambient courtyard sounds.
Image-to-video: a luxury watch rises from absolute darkness illuminated by a single warm side light — rotating slowly counter-clockwise over 10 seconds, each facet of the case and bracelet catching and releasing the light. At 10 seconds, the watch face fills frame for 4 seconds — second hand ticking. Background: matte black. Camera: static macro, very shallow depth of field. 14 seconds, 4K, luxury commercial quality. Native audio: the precise tick of the movement.
Image-to-video: a two-person fight choreography on a rooftop at blue hour — 8-hit combination: jab blocked, cross landed, grab, counter-sweep, roll, recovery, feint, roundhouse that ends the sequence. Camera cuts across the action — wide to mid to close at the final strike — with city lights below. VFX: sweat catches the air at each impact. 14 seconds, 4K. Native audio: impact sounds, heavy breathing, distant city.
Reference-to-video using 8 character reference images: a pilot in a worn exosuit walks the length of a docking bay — blast marks on the suit, a cracked visor, scorch on the left pauldron. The camera tracks from in front at a low 3/4 angle, gradually pulling back to reveal the scale of the bay and a departing ship in the far dock. 14 seconds, 4K, Aliens production design quality. Native audio: servo hum of the exosuit, distant hangar ambience.
Image-to-video: a drone shot ascending from the base of a coastal cliff at sunrise — beginning at sea level with waves crashing against rock, rising slowly through mist and spray, past the cliff face, to reveal a lighthouse and the full coastline at the top. 16 seconds, 4K. The color shifts from deep blue at the base through golden cliff-face tones to warm orange at the top. Native audio: ocean, wind intensifying with altitude, gulls at the apex.
Reference-to-video: two characters at a diner booth — the first leans forward and speaks directly to the second for 7 seconds, the second listens, then responds for 7 seconds. Reference character faces, wardrobe, and — using 3 voice clips — each character's voice signature. Lip sync to voice references. Camera: mid-shot on each speaker, low angle, warm tungsten diner light. 16 seconds, 4K. Native audio: synchronized dialogue, diner ambience, soft background music.
Image-to-video: a parkour sequence through a temperate forest trail at dawn — the athlete vaults a fallen log, drops into a gully, rolls through it, and continues at sprint pace through dappled morning light. Camera follows from behind at hip height: reactive shake through the vault and roll, smooth through the sprint. 14 seconds, 4K. Native audio: footsteps through leaf litter, impact on the log, roll sounds, birds.
Image-to-video: a slow lateral reveal of a pedestrian glass bridge spanning two city towers at night — the camera begins at the far end and tracks sideways along the structure, the city lights below shifting through the transparent floor. At mid-bridge: a single figure crosses, pausing to look down. Camera: slow steady tracking shot, slight elevation above the walkway. 16 seconds, 4K. Native audio: the hum of the city far below, wind across the bridge.
Image-to-video: a vertical ink wash scroll animation — camera pans upward from a fog-covered river valley through pine forest, waterfall, and bare rock faces to a snow-capped peak. Classical Chinese brush style: diluted ink washes, dry-brush tree detail, minimal line work on rock. 16 seconds. No color — pure monochrome on warm paper texture. Native audio: a single water drop, then silence throughout.
Image-to-video: a crystal glass falls from a marble shelf edge in extreme slow motion — the fracture point is captured at the nanosecond of contact, then the glass separates into fragments that radiate in physically correct trajectories. Camera: static front-angle at shelf height, very shallow DOF, studio white background. 14 seconds at 10% playback speed. 4K, product photography studio lighting. Native audio: the full acoustic bloom of the break at natural speed.
Image-to-video multi-shot sequence: Shot 1 (5s) — close-up of running shoes at mile 26, road-worn, the pace faltering slightly; Shot 2 (5s) — mid-shot of the runner's face, exhausted but focused, crowd noise rising; Shot 3 (6s) — wide shot of the finish line 200 meters ahead as the runner finds a final sprint. Consistent color grade across all shots: desaturated golden-hour palette. 4K, broadcast documentary quality. Native audio: continuous crowd sound threading across all three shots.
Reference-to-video using 12 character reference images: a warrior in hand-forged armor stands in a ruined throne room — morning light entering through broken stained glass casts colored shafts across the stone floor. The camera circles slowly in 8 seconds to reveal a second figure behind the warrior, stepping from shadow. 14 seconds, 4K, high-fantasy cinematic quality. Native audio: the distant echo of wind through the ruin, the second figure's footstep on stone at second 8.
Image-to-video: a close documentary sequence of ramen preparation — tare being poured from a ladle into a ceramic bowl, the tsuyu layer forming, chashu being lowered onto noodles with chopsticks, a soft-boiled egg halved and placed. Camera: static overhead for the tare, transitioning to 45-degree angle for plating. Warm LED kitchen light. 14 seconds, 4K. Native audio: liquid sounds, chopsticks, no music — pure kitchen ambience.
Image-to-video: a contemporary dancer performs a 14-second solo phrase in a white-box studio — beginning from stillness, building through a spiral to the floor, and finishing in a held balance. Camera: wide static for the full arc, transitioning to mid-shot for the floor phrase. Neutral studio white, single overhead wash. 4K, minimal aesthetic, Pina Bausch quality. Native audio: acoustic breathing and footfall on studio floor — no music.
Image-to-video: a luxury penthouse living room at sunrise — the camera begins at the entrance and glides forward as automated blinds retract to reveal floor-to-ceiling city views, dawn light flooding across polished concrete and white furniture. Camera: smooth forward dolly, no cuts. 14 seconds, 4K, architectural photography quality. Native audio: the soft mechanical sound of the blinds retracting, then ambient city sunrise.
Image-to-video: a wooden fishing vessel crests a 6-meter wave in open ocean during a storm — the bow lifts to nearly vertical, then crashes forward through the wave face, white water flooding the foredeck before draining through the scuppers. Camera: low side-angle at water level, slight slow motion at the crest. 14 seconds, 4K. Native audio: the roar of the sea, the crack of the bow, the vessel's hull straining.
Image-to-video: a timelapse-style compressed sequence of a city skyline transforming from deep night to dawn — artificial lights dimming as natural light builds from the horizon, the skyline sharpening from silhouette to full detail, clouds moving in fast motion overhead. Camera: static wide angle from above the city, very slight slow zoom over 16 seconds. 4K. Native audio: compressed night city ambient fading to birdsong at dawn.
Image-to-video: an anime-style combat sequence in heavy rain with lightning — a 5-hit exchange: two sword strikes blocked, a counter-disarm, a throw, a final strike stopped a centimeter from the opponent's face. Lightning flash illuminates the scene at the peak of the disarm. Camera: cross-cutting close to wide at each impact. Tatsuki Fujimoto visual style — high contrast black, rain streaks, ink wash atmosphere. 14 seconds, 4K. Native audio: rain, steel impacts, lightning crash at disarm.
Vidu Q4 leads for reference-count and 4K with 10-bit color — the only top-ranked model offering 15 reference inputs at 4K:
| Model | Max Resolution | Native Audio | Max Image Refs | I2V Leaderboard |
|---|---|---|---|---|
| Vidu Q4 Preview ★ | 4K (10-bit) | Yes — in-model | 15 images | #3 I2V (Elo 1,179) |
| MiniMax H3 / Hailuo 3.0 | 2K (1440p) | Yes — in-model | 9 img + 3 vid + 3 audio | #2 I2V (Elo 1,351) |
| Seedance 2.5 (ByteDance) | 4K native | Yes — co-generated | 50 multi-modal refs | Top 5 T2V |
| Kling v3 (Kuaishou) | 1080p | Limited | 5 images | #1 T2V (Elo 1,934) |
| Wan 3.0 (Alibaba) | 1080p | Yes — native | Image + video refs | #1 T2V (Elo 1,156) |
| LTX-2.5 (Lightricks) | 1080p | No | Image only | Open weights top 3 |
★ Vidu Q4 Preview: #3 globally on AA-Video-I2V v1.0 (Elo 1,179, October 2026). Launched October 7 by Shengshu Technology. Available via vidu.com, Vidu API, and YouCam. 30% launch discount through November 2026.
The Vidu Q4 prompt generator on this page gives you 20 free, copy-ready video prompts for Vidu Q4 Preview — the latest flagship AI video model from Shengshu Technology, launched October 7, 2026. Vidu Q4 Preview debuted at #3 globally on the Artificial Analysis Image-to-Video leaderboard (Elo 1,179), jumping from #19. It accepts up to 15 reference images and 3 voice clips to lock character identity, wardrobe, props, and voices across a generation, and outputs native audio in every video.
Vidu Q4 is a flagship AI video generation model developed by Shengshu Technology, a Beijing-based AI video company. Q4 Preview was released October 7, 2026 ahead of the full Q4 launch. It is an image-to-video and reference-to-video model — no text-to-video yet. Key specs: up to 15 reference images for character, wardrobe, prop, and environment consistency; up to 3 voice reference clips for dialogue and voice consistency; native audio generated with every clip; 4K output (540p to 4K, with 10-bit color at 2K and 4K); clips up to 16 seconds at 24fps; and camera controls tuned for chase sequences and action scenes.
Vidu Q4 Preview is a generation-level upgrade: (1) Resolution — 4K with 10-bit color, vs. previous Vidu models capped at 1080p; (2) Reference count — 15 reference images vs. typically 3–5 in prior versions; (3) Native audio — every generation returns synchronized sound, not just video; (4) Camera intelligence — Q4 specifically improves camera coordination in action and chase sequences, where earlier models drifted; (5) Leaderboard — Q4 debuted at #3 on AA-Video-I2V v1.0 (Elo 1,179), jumping 16 ranks in one release. The voice reference system (up to 3 clips for dialogue consistency) is also new in Q4.
Vidu Q4 parses full narrative descriptions. Use this structure: (1) Generation mode — state whether you're doing image-to-video or reference-to-video, and how many reference images/voice clips you're attaching; (2) Subject, action, and timing — describe what happens in sequence with specific timing; (3) Camera movement — describe camera position, motion style (tracking, static, aerial), and any camera reactions to action; (4) Audio intent — describe the sound world explicitly since Q4 generates native audio; (5) Resolution target — state '4K' and a quality benchmark (e.g. 'BBC documentary', 'Vogue editorial'); (6) Duration — specify clip length up to 16 seconds. For reference-to-video, name which reference locks which element: 'Reference images lock character face and wardrobe.'
Vidu Q4 Preview is accessible via the Vidu web app at vidu.com, where registered users can generate video using image-to-video and reference-to-video modes. The Vidu API provides developer access for programmatic generation. Third-party integrations include Perfect Corp.'s YouCam apps and YouCam Online Editor, which were among the first to deploy Q4. Launch pricing is $0.014 per second, with a 30% discount running through November 2026. A free tier with daily generation limits is available on the Vidu web app.
Vidu Q4 Preview, MiniMax H3, and Seedance 2.5 are three of the top five AI video models as of October 2026. Vidu Q4 leads on reference image count (15 images) and 4K resolution with 10-bit color — no other top model matches both simultaneously. MiniMax H3 leads on omni-modal input (9 images + 3 videos + 3 audio clips) and its image-to-video benchmark rank (#2 globally, Elo 1,351). Seedance 2.5 (ByteDance) leads on clip length (30 seconds) and 4K with native audio. For high-reference-count character and prop consistency in 4K, Vidu Q4 is the strongest option. For the longest clips, Seedance 2.5 wins. For combined image/video/audio reference input, MiniMax H3 is unmatched.
#2 I2V globally — 2K video, omni-modal 9-reference input, native audio
ByteDance — 4K native, 30-second clips, synchronized audio
#1 T2V globally — cinematic camera motion & long sequences
Alibaba — #1 T2V on AA leaderboard, native audio, multi-modal
Frame-level HDR control, 20-second reasoning video model
Alibaba's photorealistic cinematic AI video model
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