Kling O1 Review: A Unified Multi-Modal Video Engine Opening the Next Door on DeeVid

In the AI video space, the past few years have gone through several phases:
“Can text-to-video even work?” → “Is image-to-video more reliable?” → “Can we handle generation + editing + consistency inside one workflow?”

Kling O1 (Omni One) is built exactly for that last question — as the world’s first unified multi-modal video foundation model, it merges text-to-video, image/subject-to-video, first/last-frame video generation, reference video camera motion, video add/remove/edit, style repainting, and shot extension into one model.

From DeeVid’s perspective, this is not “just another model name.” It is:

A truly all-in-one video engine that can carry you from idea to generation, and from generation into multiple rounds of editing — all within a single semantic space.

Below, we’ll look at Kling O1’s vision, core capabilities, typical use cases, concrete skills, and what it means for DeeVid creators — as both a preview and a practical review.

What Is Kling O1? From MVL to Video O1

Kling O1’s product philosophy is MVL (Multi-modal Visual Language):

• Natural language is the semantic backbone
  Text is no longer “just a prompt,” but the main semantic spine of the whole creative process.
• Images / videos / subjects are all instructions
  Every image you upload, every clip, every “subject” is interpreted as meaningful, combinable “tokens” in O1’s eyes.
• One unified model, one semantic space
  Whether you’re generating a new video or deeply editing existing footage, everything happens inside the same large model — no more switching between sub-models and tools.

That means, once O1 is integrated into DeeVid, creators can expect a truly conversational video workflow:

You say “put this model into a snowy street at dusk, with a film-like look, medium shot pushing in,” and the model reconstructs pixels according to your semantic logic — instead of you manually keyframing, masking, and stacking effects.

Five Key Highlights in Kling O1

1. All-in-one Engine: A Unified Video Foundation Model

The first highlight of Video O1 is that it pulls together tasks that used to be scattered across different tools:

• Reference-based video generation (image to video ai/ subject-to-video)
• Pure text to video ai
• First/last-frame-to-video (interpolating the in-between)
• Adding / removing content in video
• Video transformation (background, weather, material, perspective…)
• Style repainting (from realistic to cyberpunk, ink wash, pixel art, etc.)
• Shot extension (previous shot / next shot)

For DeeVid users, that directly means:

• You don’t have to switch between a “generation tool → editing tool → keying tool → style plugin” chain.
• From the initial draft all the way to multiple revisions, a shot can stay in O1’s semantic space the whole time, with context preserved.

2. Universal Instructions: Text + Multi-Modal Input = True “Conversational Post-Production”

In Kling O1, everything you upload is treated as instruction:

• Images
• Videos
• Subjects (built from 1–4 multi-view images)
• Text

All of them are instructions.

You can use very natural language in English (or Other Major Languages) to do what used to be advanced post-production work, for example:

• “Remove the passerby in the background”
• “Turn daytime into dusk”
• “Change it to pixel art style”
• “Make the protagonist’s coat a long red trench coat”
• “Replace the background with a snowy mountain town”

The model reads your text + media, and performs pixel-level semantic reconstruction, without you drawing masks, setting keyframes, or stacking filters.

Inside Kling O1’s multi-modal input area, you can do, among other things:

• Image / subject reference
  • Use roles / props / scenes from your reference images to generate creative footage
  • For example, “use these three model photos + this clothing photo to create a runway video”
• Instruction-driven transformation (editing existing video)
  • Add / remove content
  • Change shot type / perspective (long shot, medium shot, close-up, over-the-shoulder, etc.)
  • Modify subject / background / local regions / style / color / weather
  • Green-screen keying (replace the background with green while preserving specific subjects)
• Video reference
  • Generate the “previous shot” or “next shot” based on an existing clip
  • Transfer a clip’s camera motion onto an image or a set of images
  • Take the motion of a character in a video and make a character from an image “move the same way”
• First/last-frame control
  • Design start and end frames and describe what happens in between
• Pure text-to-video
  • Use a prompt template like “subject + action + scene + camera language + lighting + mood” to generate a complete shot.

From DeeVid’s point of view, this is essentially second-generation prompting:
No longer “add more adjectives,” but “describe your shot using full audiovisual language.”

3. Universal Reference: Actually Solving the “Video Consistency” Problem

One of the biggest headaches in AI video generator has been consistency:

• Character faces fluctuate wildly;
• Clothes lose or gain random straps and pockets;
• Props and scenes morph from shot to shot.

Kling O1 reinforces understanding of input images and videos at the model level, and introduces the concept of a “subject” — built from up to 4 multi-view images, representing one character or object. You can then reuse that subject across multiple shots:

• The model “remembers your main character / props / scene” like a human director;
• Even when camera angles and shot types change, key subject features stay stable;
• When using reference images / subjects across shot sequences, consistency improves drastically.

Within DeeVid’s multi-model lineup, Kling O1 is ideal for consistent long-term character / product shots, especially for brand mascots, virtual IPs, and e-commerce brands.

4. Powerful Combinations: Skills That Stack

A very practical but easily overlooked point:
O1 is not “a list of isolated features” — it lets you stack them together. For example:

• Add a new subject to a video while also changing the overall style;
• Use reference images to generate a shot while also rewriting local style;
• Perform multiple localized add/remove/edit operations in one instruction;
• During reference-based generation, simultaneously specify style / weather / material / color, etc.

For DeeVid, this is huge, because we can wrap these “composite tricks” into templated workflows, so creators choose by scenario instead of manually crafting every single prompt from scratch.

5. Control Over Rhythm: 3–10 Seconds of Free Storytelling

Kling O1 supports 3–10 seconds of video per generation.

This might look like a technical parameter, but it hits something fundamental in video: rhythm.

• 3–5 seconds: great for strong visual hits, B-roll, and transitions;
• 6–8 seconds: enough to cover a complete movement, a line of dialogue, or a mood beat;
• 9–10 seconds: can carry a mini-beat with beginning, build-up, and resolution.

In DeeVid’s editing context, we prefer treating O1 outputs as “shot material pool”:
Generate short, well-crafted motion and emotion clips, then stitch them into a longer piece on the timeline. The result is more controllable and more efficient.

Typical Use Cases: Four Ways O1 Shows Up in Real Workflows

1. Film / Narrative: From Storyboard to Multi-Shot Sequences

With image/subject reference + subject library, filmmakers can:

1. Use DeeVid’s image models to generate character designs and costume/prop views;
2. Combine those into one “subject,” and generate multiple shots in O1;
3. Use “previous shot / next shot” to maintain continuity in scene, composition, and mood.

This greatly reduces pre-viz / storyboard cost:
You don’t have to hand-draw every frame — AI can generate “editable, cuttable” video references.

2. Creative Ads: Product Photo + Model + Scene = One Commercial

Traditional offline ad production has very real pain points:

• High production costs: location, gear, lighting, crew…
• Long cycles: from concept to shoot to post, often weeks or even months.

In Kling O1, the pipeline for a product/brand video can become:

1. Upload product photos + model shots + environment images;
2. Describe camera moves, pacing, and overall style with natural language;
3. Generate multiple versions of product showcase videos in one go.

For DeeVid users, that means:

Small teams and solo sellers can create ad-like footage that looks close to professionally shot commercials, and actually experiment with creative variations.

3. Fashion & Outfit: A Virtual Runway That Never Closes

Fashion brands face recurring challenges:

• Booking models is complex;
• Every outfit, every location change means another shoot;
• It’s hard to quickly build a strong sense of series consistency.

Kling O1’s “model + clothing photo + instruction → Lookbook video” flow is ideal for DeeVid to package into fashion templates:

• Use a model subject + multiple outfit images to batch-generate runway / street / fitting-room shots;
• Produce a complete new collection in one go with consistent characters and styling;
• Quickly adapt aspect ratios and styles for different platforms (TikTok, Instagram, Xiaohongshu, etc.).

4. Video Post-Production: Complex Timelines and Masks Collapsed into One Sentence

In traditional post tools, removing a person or changing a sky means:

• Drawing masks；
• Tweaking tracking, feathering, color;
• Previewing and fixing repeatedly.

Kling O1’s natural language editing collapses all that into a single instruction:

• “Delete the passerby in the background”
• “Turn the sky into a soft purple sunset”
• “Change the distant buildings into a cyberpunk city”

The model uses deep semantic understanding to perform pixel-level repair and reconstruction.
Combined with a simple timeline in DeeVid, this becomes a kind of “AI After Effects Lite” for many creators.

Skill-Level Breakdown: Helping DeeVid Users Use O1 Clearly

1. Image / Subject Reference

• Upload 1–7 images / subjects when no video is present, each at least 300 px in width/height, up to 10 MB, format jpg / jpeg / png;
• If a video is present, images + subjects can total up to 4;
• A subject consists of up to 4 multi-view images, giving the model a more complete 3D understanding.

For DeeVid’s real usage, we recommend:

• For products / characters, try providing front, side, and 3/4 view;
• Add at least one close-up for important details (logos, textures, hairstyles, accessories);
• Keep lighting somewhat consistent to help the model build a coherent appearance.

2. Instruction Transformation: Editing Existing Video

With combinations of text + images + subjects, Kling O1 can perform rich edits on an existing video:

• Add content
  • “In @video, add the content from @image”
  • “In @video, add a blue whale floating in mid-air”
• Delete content
  • “Remove the passerby in the background of @video”
• Switch viewpoints / shot types
  • “Generate a frontal close-up version of @video”
  • “Generate a long shot from above of the same scene”
• Modify subject
  • Replace by text (change hair color, clothes, species, etc.)
  • Replace via images/subjects (swap A for the protagonist from reference image B)
• Modify background
  • Replace with a described environment
  • Or use another image as the target scene (cave, snowfield, cityscape, etc.)
• Modify local regions
  • E.g., “only change the sword blade’s style,” “only change the sky and weather”
• Modify style
  • U.S. cartoon, Japanese anime, cyberpunk, pixel art, ink wash, watercolor, figurine style, etc.
  • Or use another image’s style as the global style reference;
• Modify color / weather / material
  • “Turn the car into a red metallic finish”
  • “Change the scene to heavy snowfall”
• Green-screen keying
  • “Change @video’s background to green screen, keeping the character and jellyfish”

You can think of this as:

An AI paintbrush on the timeline, spanning what used to be multiple tracks and plug-ins in traditional tools.

3. Video Reference: Shot Extension and Motion Transfer

• Generate the next shot
  • “Based on @video, generate the next shot: [describe content]”
• Generate the previous shot
  • “Based on @video, generate the previous shot: [describe content]”
• Reference camera motion
  • “Use @image1 as the first frame, and apply @video’s camera motion onto it”
• Reference character action
  • “Use the girl’s motion in @video to animate the girl in @image1”

For DeeVid users, this is especially useful for:

• Multi-shot storytelling in narrative shorts / commercials;
• Motion transfer from live-action to virtual characters (VTubers, virtual idols, game characters, etc.).

4. First / Last Frame: “Writing” the In-Between Between Two Images

• Specify “Use @image1 as the first frame, [describe how the scene changes]”;
• Or designate both first and last frames and describe the transition between them.

This is particularly suitable for:

• Turning static product posters into dynamic reveals;
• Transforming one portrait into another style / scene;
• LOGO animation intros.

5. Text-to-Video: Prompt Templates for “Cold Start”

With no media provided, you can generate a shot with text alone.
A recommended structure is:

Subject (who) + motion (doing what) + scene (where) + camera language + lighting + atmosphere

For example:

“In a slow-motion cinematic shot, a fashion model is wrapped in a flowing cloak made of glitch art patterns. Against a dark background, a strong spotlight brings out the texture of the fabric. The model’s face is partly covered by the glitch cloak, showing a calm, transcendent expression, eyes fixed on a point outside the frame.”

Storing this kind of template in DeeVid’s prompt library can drastically reduce trial-and-error time for new users.

Input Limits and Pricing: Where the Boundaries Are (For Now)

Input Specs (Internal Beta)

• Images
  • Up to 7 images, width/height ≥ 300 px, ≤ 10 MB each, jpg / jpeg / png;
• Video
  • One clip only, 3–10 seconds long, ≤ 200 MB, resolution ≤ 2K;
• Subjects
  • Each subject built from up to 4 multi-view images;

Rules:

• When a video is present: total images + subjects ≤ 4;
• When there is no video: total images + subjects ≤ 7.

On DeeVid, we’ll implement necessary size and count validation on the front end, so users don’t hit invisible limitations after upload.

Pricing (Beta Info)

• In the official beta, Video O1 is priced at 10 “Inspiration Points” per second, as a non-final price.
• Official pricing will be announced upon public release;
• On DeeVid, this will be mapped into our own credit / billing system — final pricing will follow DeeVid’s published model.

DeeVid’s Perspective: What Does O1 Bring to Our Product?

For DeeVid, Kling O1 isn’t about a single “killer trick,” but a full chain of capabilities:

1. From multi-modal understanding
   • It brings images, videos, subjects, and text into a genuinely shared semantic space.
2. From creative workflow
   • It turns “generate → edit → extend” into one seamless, dialogue-driven process.
3. From scenario coverage
   • It addresses film, commercials, e-commerce fashion, and post-fixing with one model.
4. From platform architecture
   • It lets DeeVid design a set of O1-driven “template workflows,” packaging complex capabilities into one-click solutions.

You can think of O1 as a crucial puzzle piece in DeeVid’s future video stack:

• When you want to create a brand-new shot from scratch: use text-to-video + image/subject reference.
• When you want to upgrade an existing clip from 1.0 to 1.5: use instruction-based transformation (natural language editing).
• When you want to tell a complete story: treat O1 as a “shot factory,” then assemble on DeeVid’s timeline.
• When you want to build a consistent character / brand world: leverage subject libraries and multi-shot consistency to unify character and style.

Shifting from “one more model in the toolbox” to “one more creative engine in the platform” — that’s how DeeVid sees Kling O1.

Practical Tips for DeeVid Creators

If you’re a DeeVid creator, here’s a simple mental model for using O1:

1. Need a shot from zero?
   → Start with text + image/subject reference.
2. Need to enhance existing footage?
   → Use instruction-based transformation (natural language editing).
3. Need a full sequence or story?
   → Use O1 as a “shot generator,” then cut and arrange in DeeVid’s editor.
4. Need a consistent series / brand character?
   → Build subjects and reuse them across shots to unify look and feel.

As DeeVid’s integration with Kling O1 deepens, we’ll roll out more O1-powered preset templates and scenario workflows inside the product — so this unified multi-modal video engine can quietly become part of your everyday creative toolkit.