MWONGOZO wa Makampuni
Kling na Kuaishou
Kling AI is the video generation model family and app made by Kuaishou, the Chinese short-video company, first announced in June 2024.
Sikiliza mwongozo huuInaonyeshwa na AI · ~7 min
Katika ukurasa huudk 8 kusoma
Muhtasari
It turns text, images, reference clips and audio into short videos and has become one of the most commercially successful AI video products, with Kuaishou reporting an annualized revenue run rate of about USD 500 million in March 2026.
Mambo muhimu ya kuchukua
- Kling AI is Kuaishou's family of video generation models, announced on June 6, 2024 and sold through subscriptions and an API.
- Kuaishou describes Kling as a diffusion transformer with a self-developed 3D VAE that compresses video across space and time.
- Kling 2.6 and the O1 model in December 2025 added joint audio-video generation and unified editing and referencing.
- The Kling 3.0 series launched on February 5, 2026 with clips of up to 15 seconds and multimodal inputs and outputs.
- Kuaishou reported Kling revenue of over RMB 850 million in Q2 2026, up more than 200% year on year.
Dive ya kina
Kling AI is a family of generative video models, together with the web and mobile apps that expose them, built by Kuaishou Technology, the company behind the Kuaishou short-video app. Given a text prompt, one or more images, reference videos or audio, Kling produces a short video clip. Later versions also edit existing video and generate synchronized sound. Kuaishou sells access through consumer membership subscriptions and through API services for businesses and developers, and it reports Kling's revenue separately in its quarterly results, which makes it one of the few AI video products with public financial numbers.
Under the hood, Kling follows the same broad recipe as other modern video generators. Kuaishou's June 2024 launch release says the model uses a diffusion transformer (DiT) architecture. A diffusion model learns to turn random noise into a realistic sample step by step, and a transformer is the attention-based network design used in large language models; a DiT uses a transformer as the denoising network. The release also describes a self-developed 3D variational autoencoder (VAE), a network that compresses video into a smaller latent representation across both space and time so the diffusion model works on compact codes rather than raw pixels, and a full-attention mechanism that models spatial and temporal information together. Kuaishou has not published a full technical paper on the production models, so details beyond these descriptions are not public.
The product history is dense. Kuaishou announced Kling on June 6, 2024, claiming clips of up to two minutes at 30 frames per second and up to 1080p. Access was initially limited. When MIT Technology Review's Zeyi Yang tested it that month, he needed a Chinese phone number and a waitlist, his clips were capped at five seconds and appeared to be 720p, and each took about three minutes to generate. By Kuaishou's own count the model went through more than 20 iterations in its first year. Version 2.0 rolled out globally in April 2025, and the 2.1 series arrived at the end of May 2025 with a 720p standard mode, a 1080p high-quality mode and a premium Master edition.
The next steps added sound and unified inputs. In early December 2025 Kuaishou released Kling Video 2.6, which generates audio and video together, and Kling Video O1, which it describes as a unified multimodal model for generation, editing and video referencing, with a subject library to keep characters and objects consistent. On February 5, 2026 it launched the Kling 3.0 series, covering video and image models with Omni variants. Kuaishou's Q1 2026 report describes 3.0 as an all-in-one framework that accepts and produces text, images, audio and video, supports clips of up to 15 seconds and adds storyboard control. In Q2 2026 it added Kling 3.0 Turbo and native 4K output. fal, a model hosting company, reported that a Kling 4.0 Flash preview opened to a limited group on September 28, 2026, with the full 4.0 model set for October 2026 and generations of up to 30 seconds.
The business numbers explain Kuaishou's attention. The company said Kling passed USD 100 million in annualized revenue run rate, defined as one month's revenue times 12, in March 2025, ten months after launch. It reported USD 240 million in December 2025, with over 60 million creators, more than 600 million videos generated and over 30,000 enterprise users. Quarterly Kling revenue reached over RMB 650 million in Q1 2026, up more than 300% year on year, and over RMB 850 million in Q2 2026, up more than 200%. Kuaishou calls Kling its second growth curve.
Compared with alternatives such as OpenAI's Sora and Google's Veo, Kling competes on the same axes: motion quality, prompt following, clip length, resolution, consistency of characters across shots, and native audio. Direct, independent comparisons are hard because vendors release hand-picked demos and models change every few months. The Technology Review test in 2024 noted exactly this problem, contrasting Sora's curated showcase clips with Kling's first-attempt results. Kuaishou has emphasized long maximum durations and reference-driven consistency, and Technology Review suggested its large video platform could give it a training-data advantage.
Limitations are those of the whole field plus some specific to Kling. Early tests found blurry, grainy output that sometimes ignored large parts of the prompt, and an expert quoted by Technology Review noted that longer videos are more prone to inconsistency. Kuaishou has said only that it trains on publicly available data, so the training set is not documented. In that 2024 test English-only prompts did not work; version 2.0 later rolled out globally in April 2025.
In practice, using Kling requires an account on the Kling AI website or app and, for heavier use, a paid membership; businesses use the API. New capabilities can reach a limited group before everyone else, as with the early access preview of Kling 4.0 Flash. Teams can collaborate in a Team Plan of up to 15 members, according to the Q1 2026 report. Because model versions change quickly, the safest approach is to check the current release notes for duration, resolution and audio limits before planning a production around them.
04Mfano uliofanya kazi
Planning a short product shot with Kling
Check the current Kling release notes for the model version you can access, and write down its maximum duration, resolution and whether it generates audio.
Write a prompt that names the subject, setting, camera movement and lighting, for example a slow dolly-in on a ceramic mug on a wooden table in morning light.
Upload one clean product photo as an image reference so the object's shape and label stay consistent.
Generate several short variants at the lowest resolution first to save credits, and note which prompts the model followed or ignored.
Pick the best variant and regenerate it at the target resolution, adding a sound description if the model supports audio.
Review the final clip frame by frame for warped text, changing object shape or impossible motion before using it.
Nini inaonyesha
A short clip that matches the reference product, plus notes on which prompt details the model obeyed. If the label text or object shape drifts between frames, add more references or shorten the clip.
Utekelezaji wa Ulimwengu Halisi
Visual effects work on the series House of David, where Kuaishou's Q1 2026 results say Kling tools produced hundreds of shots including battle scenes, and on the Chinese historical drama Swords Into Plowshares.
Businesses and developers calling Kling through API services, which Kuaishou said in June 2025 served over 10,000 corporate clients and developers in advertising, film, animation and game production.
Agent-driven batch production using Kling MCP and Kling CLI, launched in Q2 2026 so that AI agents can orchestrate Kling for content creation and workflow automation.
Advertising production, where two Kling-generated ads won one Silver and two Bronze Lions at Cannes Lions 2026, according to Kuaishou's Q2 2026 results.
Live-streaming gifts on the Kuaishou app that use Kling video generation; Kuaishou reported users sent over 6 million of these AI gifts in Q2 2026.
Mustakabali wa Kling na Kuaishou
Kuaishou's own statements point to its priorities. Its Q2 2026 results, released August 19, 2026, say the company plans to scale Kling's model capabilities and expand adoption in professional creative work such as film, television and advertising. Recent releases show the direction: longer single generations, from 15 seconds in the February 2026 3.0 series to a reported 30 seconds for Kling 4.0 according to fal's 2026 write-up, native 4K output, synchronized audio, and multi-reference control to keep characters consistent across shots. The launch of Kling MCP and Kling CLI in Q2 2026 suggests more use by AI agents that assemble videos automatically. Open problems are shared across the industry: physical plausibility over long clips, reliable text rendering, transparent training data, and independent evaluation that is not based on curated demos.
Kuiweka katika vitendo
Kwa nini ni muhimu
- Mkakati wa muuzaji. Ramani za barabara za wachuuzi huathiri vipengele ambavyo timu yako inaweza kuunda baadaye.
- Gharama na bajeti. Masharti ya kibiashara na chaguzi za kupeleka huathiri gharama na hatari ya muda mrefu.
- Hatari na usalama. Vivutio vya kampuni hutengeneza chaguo-msingi za bidhaa, mkao wa usalama na uwazi.
Jihadharini na
- Matangazo ya uzinduzi yanaweza kushinda uthabiti katika utendakazi halisi wa uzalishaji.
- Bei za API au mabadiliko ya sera yanaweza kuvunja mawazo mara moja.
- Utegemezi wa muuzaji mmoja huongeza gharama za kufunga na kuhama.
Hatua zinazofuata
- Tathmini watoa huduma kwa kutumia kazi na seti zako za data.
- Kagua faragha, usalama na masharti ya kisheria kabla ya kuunganishwa.
- Dumisha mpango mbadala kwa miundo au wachuuzi.
- Fuatilia maelezo ya toleo ili mabadiliko ya ramani ya barabara yasiwashangaze timu.
Vyanzo na kusoma zaidi
- TechNode Global (PR Newswire Asia)Kuaishou Unveils Proprietary Video Generation Model 'Kling;' Testing Now Available
- MIT Technology ReviewI tested out a buzzy new text-to-video AI model from China
- PR Newswire (Kuaishou)Kling AI Celebrates First Anniversary; Achieves Annualized Revenue Run Rate Surpassing USD100 Million in 10th Month Since Launch
- PR Newswire (Kuaishou)Kling AI Annualized Revenue Run Rate Hits USD240 Million in December 2025
- PR Newswire (Kuaishou)Kuaishou Technology Announces First Quarter 2026 Unaudited Financial Results
- PR Newswire (Kuaishou)Kuaishou Technology Announces Second Quarter and Interim 2026 Unaudited Financial Results
- falWhat is Kling 4.0? Everything You Need to Know
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Jijaribu mwenyewe
Take the Kling by Kuaishou quiz
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Maswali yanayoulizwa mara kwa mara
What is Kling by Kuaishou?
Kling AI is the video generation model family and app made by Kuaishou, the Chinese short-video company, first announced in June 2024. It turns text, images, reference clips and audio into short videos and has become one of the most commercially successful AI video products, with Kuaishou reporting an annualized revenue run rate of about USD 500 million in March 2026.
Je, ni kampuni gani iliyotengeneza modeli ya kutengeneza video ya Kling?
Kling ilitengenezwa na Kuaishou, kampuni ya Kichina inayojulikana kwa jukwaa lake la video fupi.
What capability did Kuaishou announce for Kling Video 2.6 in December 2025?
Kuaishou announced that Kling Video 2.6 adds text-to-audio-visual and image-to-audio-visual generation.
Which generation and editing tasks does Kuaishou list for the Kling 3.0 model series?
Kuaishou’s February 2026 announcement lists text-to-video, image-to-video, reference-to-video, and in-video editing in the 3.0 workflow.
What maximum video duration did Kuaishou announce for Kling Video 3.0?
Kuaishou’s February 2026 3.0 announcement describes video generation up to 15 seconds; limits are version-specific.
What motion-control capability did Kuaishou describe for Kling 2.6?
Kuaishou’s 2025 year-end results describe Kling 2.6 motion control as replicating motion from uploaded videos or an online motion library.
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