kling-v2-master is the V2 Master video model in Kuaishou's Kling series, designed for short-shot creation starting from text concepts or a first-frame image, with a balance between visual quality and user experience. It is suitable for product showcases, concept storyboards, and animated photo assets, and can also handle animation tasks in talking-photo workflows. When choosing, focus on single-shot expression rather than multi-asset editing or native audio-video generation.
Clarify capacity, inputs and outputs, and invocation methods before selecting.
The above duration, aspect ratio, and asset requirements apply to this platform's invocation scope. Talking photos are a combined creation workflow and are not equivalent to the model's native audio.
Learn what kling-v2-master can bring to your work.
Text-to-video is suitable for turning scene descriptions into watchable shot drafts. When creating, you can organize prompts around the subject, action, environment, and lighting, focusing a piece of content on one clear event. The balanced positioning of V2 Master is suitable for comparing different creative expressions, then using selected results for storyboard discussions or subsequent editing.
Image-to-video uses an existing image as the opening foundation, then describes the desired action through prompts. Compared with starting entirely from text, this approach lets product images, portraits, or scene designs participate directly in creation. It emphasizes developing the image from a specified starting point and does not provide end-frame locking, making it more suitable for short shots where the ending is allowed to develop freely.
The talking photo workflow accepts a portrait photo and existing audio, first animates the photo, and then processes lip synchronization according to the audio. After specifying V2 Master, it handles the animation generation portion. This workflow is suitable for character introductions or short spoken presentations with existing voiceovers, without mistakenly writing dialogue as instructions for the video model to generate sound automatically.
Start with specific tasks to find where the model can be effective.
Input a product display image and describe a slight rotation, background atmosphere, or presentation action to generate dynamic clips for short-video editing. You can choose a landscape, portrait, or square aspect ratio based on the placement, then add selling-point captions and music during editing. It is recommended to highlight one display focus at a time rather than arranging an entire advertising storyline within the same shot.
Organize an individual scene from a script into descriptions of the subject, action, and environment, and use text-to-video to create shot drafts; when art direction already exists, you can also start from a scene image. The deliverables are short clips that facilitate team discussion, suitable for comparing mood, composition, and action expression before deciding which content enters formal production or manual refinement.
Prepare a clear front-facing photo of one person and a voiceover, then use the talking photo entry to create character introductions, character greetings, or brief explanations. The audio should fit within the selected video duration, and prompts should mainly describe expressions and movements. Once complete, obtain the final video link and integrate it into existing content publishing or editing workflows.
Choose based on task complexity, input materials, and expected results.
V2 Master is suitable for short-shot tasks driven by text or a first frame; V2.1 Master places greater emphasis on quality and consistency. Both use a single mode here, with durations of 5 or 10 seconds, and neither provides an end frame, audio accompaniment, or structured camera movement. If visual consistency is important, compare results using the same materials rather than treating version numbers as a direct guarantee of results.
If the task must lock the ending image, consider V2.5 Turbo pro, which supports end frames; if synchronized audio accompaniment is needed, choose V2.6 pro or V3. Multiple images, reference videos, and existing video editing are better suited to O1 or V3 Omni. The value of choosing V2 Master lies in its clear text-to-video and first-frame creation workflow, not in covering these different control requirements.
From a small-scale task to formal integration.
Define the goal, required inputs, and output requirements, and use real business examples as a starting point.
Open the trial page, confirm the parameters supported by this entry point, then submit a small-scale task to view the results.
Keep the complete model ID, use the request format specified in the documentation, and confirm billing rules on the Pricing page.
Before formal use, understand the output quality and capability scope.
Answers to common questions when using kling-v2-master.
Explicitly specify model=kling-v2-master in /kling/videos or /kling/talking-photo. This clearly selects V2 Master instead of relying on the default value of the endpoint. kling-v2-1-master is another model and should not be used as an alternative name for the same model.
Use /kling/videos, set action to image2video, provide start_image_url, and use prompt to describe the action and scene changes. Simply choose a duration of 5 or 10 seconds. This model does not support end-frame control, so when creating, treat the first frame as the starting point rather than constraining both the start and end points.
You cannot use a video prompt as speech generation input. To create a talking photo, provide image_url and audio_url to /kling/talking-photo; prompt is used for movements or expressions during the photo animation stage. It is recommended to prepare the voiceover first, then have the photo lip-sync to that audio.
This model generates videos of 5 or 10 seconds, and talking photos also offer these two duration options. Longer content can be split into shots and then edited together; if you need more flexible single-generation durations, consider V3 rather than passing arbitrary seconds to V2 Master.
You can use async=true to obtain task_id, then query the task result; you can also set callback_url to receive completion notifications. Applications should associate the task ID with the creation record, then read state and video_url after completion. Successful task submission and completed video generation are different stages and should not be treated as the same status.
Model information · Updated: 2026-10-01. For call parameters and billing rules, see the API and pricing sections.
Start with a clear goal, and judge from actual results whether it suits your work.
Pricing
$1.33–$2.66· per second
You pay$13,584for 142,800 credits · $0.0951 / credits46% OFF
You're billed in credits. Pick a top-up tier to see its per-credit rate — the larger the top-up, the cheaper each credit.
This is only a basic call example. See the full docs for more parameters and advanced usage.
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