Huawei Cloud Software / SaaS Global Translated from Chinese

Wanxing Technology (万兴科技)

Wanxing Technology needed to reduce the cost of API-based video generation, gain more control over model quality, and secure enough AI compute to support very high global demand for AIGC video features.

30+ professional camera movements
average cost per generated video reached RMB 1.2
average daily cost for 100,000 externally generated videos was RMB 120,000
average daily demand exceeded 1 million generated videos

Reported impact

Business outcome

The project gave Wanxing a proprietary AIGC video-creation platform with controllable generation features and a path away from expensive third-party video APIs, while scaling the model foundation for global creative products.

  • Cost Reduction
  • Scalability
  • Speed to Market

Solution

Wanxing Technology partnered with Huawei Cloud to replace costly external API-based generation with a unified AI-and-cloud foundation for its video-creation products. Ascend AI Cloud Service supplies the training and inference compute base, while the Pangu multimodal large model provides the generative layer used to build Wanxing Tianmu 2.0. On top of that foundation, Tianmu 2.0 exposes six controllable video capabilities: image-to-video, video continuation from first and last frames, reference-based generation, controllable video generation, video editing, and audio-video synchronization. User prompts, images, and video frames are fed into the multimodal pipeline, which produces motion-controlled clips and synchronized sound effects for creative applications. The architecture is built for very high throughput because Wanxing says its AIGC products already see more than one million video-generation requests per day.

Data flow

Text prompts, first and last frames, and reference assets enter Tianmu 2.0 on top of the Pangu multimodal model and Ascend compute, where the system generates or extends video, edits motion, and synchronizes audio. The outputs are then served into Wanxing's AIGC creative software portfolio for end users.

Solution architecture

3 components · 2 layers
  1. Compute
    • Ascend AI Cloud Service Provides the AI compute foundation for training and serving Wanxing's video-generation models.
    • Pangu multimodal large model Serves as the core multimodal generative-model layer used to build Wanxing's video capabilities.
  2. Serving
    • Tianmu 2.0 Delivers the controllable audio-video generation, continuation, editing, and synchronization features to end users.

Architecture clues

  • The deployed capability set includes image-to-video, continuation, reference generation, controllable generation, video editing, and audio-video sync.
  • The source describes a unified AI and cloud foundation built on Huawei Cloud.
  • The workload is sized for more than one million generated videos per day.
  • Tianmu 2.0 is supported by a hundred-billion-parameter Pangu model and Ascend AI compute.

Evidence from the source

"Tianmu 2.0 supports more than 30 professional camera motions and 7 aspect ratios. (original: 支持推进/拉远,右移/左移,升起/下降,上摇/下摇,放大/缩小,30+专业运镜方式;兼容7种长宽比画面比例(行业领先);)"
"Using Ascend AI cloud service as the compute base and the Pangu multimodal large model, Wanxing derived six controllable advanced video capabilities including image-to-video, continuation, reference generation, controllable generation, video editing, and audio-video synchronization. (original: 万兴科技以华为云昇腾AI云服务为算力底座,基于盘古多模态大模型,衍生出图生视频、视频续写、参考生成、可控视频生成、视频编辑、音画同步六大可控视频高阶能力。)"
"Wanxing Technology worked with Huawei Cloud to build a unified AI and cloud foundation based on the Pangu large model and keep pushing audio-video large-model innovation into production. (original: 万兴科技携手华为云,基于盘古大模型构建统一AI与云底座,持续推进音视频大模型技术创新与数字创意应用落地。)"
"Wanxing says its AIGC creative software has reached more than 1.5 billion users in over 200 countries and regions, and Tianmu alone sees more than one million video-generation requests per day. (original: 万兴科技是全球领先的新生代数字创意赋能者,拥有多款AIGC创意软件,在全球累计覆盖超15亿用户,遍布200多个国家和地区。以万兴天幕大模型为例,其具备首、尾帧生视频、视频续写等功能,平均每天有上百万条视频的生成需求。)"
"When AI video generation relied on external APIs, the average daily cost for 100,000 generated videos was RMB 120,000, or RMB 1.2 per video. (original: AI视频生成依赖外部API能力,每天平均10万条视频生成成本12万元,平均每条视频生成成本达到1.2元。)"
Transparency Evidence & methodology 96/100 reference value · 81% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value96/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence81%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Huawei Cloud

    万兴科技:携手盘古视频生成大模型,打造业界领先的AIGC视频创作平台_华为云

    First-party
    https://www.huaweicloud.com/cases/wandershare.html
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.