SeaArt AI had to serve a fast-growing generative-image platform with millions of active users, hundreds of thousands of models, and highly variable combinations of base models, LoRA adapters, and ControlNet pipelines. The company needed lower-latency inference, cheaper end-to-end model scheduling, and faster model reads so user experience would not collapse under queueing and asset churn.
Reported impact
Alibaba Cloud helped SeaArt move from queue-heavy image generation to a faster, more elastic serving stack. Model inference time fell to 3.95 seconds, end-to-end performance still improved more than 50% even after model-read overhead was counted, and the platform could keep serving more than 10 million active users across a catalog of over 300,000 models and more than 1 billion image-video assets.
SeaArt AI rebuilt its image-generation serving path on Alibaba Cloud around DeepGPU, ACK AI Suite, Fluid, and OSS acceleration. DeepGPU improves single-node inference performance for the image-generation stack, reducing the compute cost of core model execution relative to both native PyTorch and xFormers-style baselines. To tackle end-to-end bottlenecks instead of only kernel speed, SeaArt also adopted Fluid as a distributed model-cache layer in the inference-node memory tier, where hot models can be expanded or replaced through LRU-style cache management. OSS Accelerator complements that layer by raising throughput for model reads when assets are not already resident in memory. Together those components let SeaArt serve a huge model catalog with much less waiting during model and LoRA switching, while preserving enough elasticity to support a global AI-creation platform whose asset inventory and concurrency requirements keep changing.
User prompts are routed into the ACK AI Suite serving layer, where the requested base models, LoRA adapters, and ControlNet assets are fetched either from Fluid's distributed cache or through OSS Accelerator. DeepGPU then executes the model inference path and returns images to the user-facing creation workflow with lower latency and less queue-induced degradation.
DeepGPU improved inference 2.5 to 6 times versus native PyTorch and 1.5 to 2.3 times versus xFormers. (original: DeepGPU 相较原生 PyTorch 推理性能提升 2.5-6 倍，相较社区级领先框架 xFormers 推理性能提升 1.5-2.3 倍。)
SeaArt AI serves more than 10 million active users worldwide, with more than 1 billion image and video assets and more than 300,000 models. (original: 目前，海艺 AI 在全球已积累超过 1000 万活跃用户... 拥有超过 10 亿的优质图像视频素材，模型数量超过 30 万。)
To handle diverse user requests, SeaArt needed an efficient and cost-effective inference cluster and had to optimize model scheduling plus read or write performance. (original: 海艺 AI 需要一套高效且具备性价比的解决方案来构建用户服务推理集群，这不仅需要在单点推理性能上进行极致优化，还需要进一步优化端到端多样模型组合的调度与读写能力。)
With DeepGPU plus Fluid and OSS acceleration, SeaArt reduced inference time to 3.95 seconds and still improved overall end-to-end performance by more than 50%. (original: 阿里云的 DeepGPU 方案，帮助海艺 AI 的推理耗时提升至 3.95 s... 对比原架构的 8-10 s 性能提升 50% 以上，端到端性能... 整体提升依然在 50% 以上。)
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
Related
Alibaba Cloud Sample Oct 12, 2026 ECLICKTECH (易点天下) ECLICKTECH needed to industrialize AI-driven advertising operations, but media-delivery workflows were still long, manual, and heavily dependent on senior operators for anomaly diagnosis and creative adaptation. As more… AI covers about 50% of core execution work AdClaw · AgentCore · AgentLoop Alibaba Cloud Sample Oct 8, 2026 ECLICKTECH (易点天下) ECLICKTECH's operations team had to manage a multi-cloud, multi-product environment that supported several lines of business, but its observability data, alerting systems, and AI tooling were fragmented across separate… connects more than 600,000 media outlets globally AgentCore · AgentLoop · Cloud Monitor 2.0 Alibaba Cloud Sample Jul 28, 2026 Zhuiyin Technology (追因科技) Zhuiyin Technology had already built an agent for cross-border ecommerce analysis, but once the agent was exposed to customers, the team discovered three hard problems: results were hard to judge objectively, reasoning… inference quality improved 20% AgentLoop · Trekin Agent 