
專項更強Optimizes serverless pipelines specifically for generative media models, but lacks general-purpose PyTorch training studios.
GreenNode 每月有 75,996 次造訪,月增率 +28.1%,定價模式為付費。Lightning AI 每月有 272,562 次造訪,成長率 -12.3%,定價模式為免費增值、付費、需聯絡報價。
| 面向/指標 | ||
|---|---|---|
| 官方網域 | greennode.ai | lightning.ai |
| 定價模式 | 付費 | 免費增值、付費、需聯絡報價 |
| 每月造訪次數 | 7.6萬 (75,996) | 27.26萬 (272,562) |
| 月流量變化量 | +1.67萬 (+28.1%) | -3.81萬 (-12.3%) |
| 主要市場與市佔 | 🇻🇳 越南 (76%) | 🇺🇸 美國 (31.8%) |
| 每月直接造訪 | 4.19萬 | 14.21萬 |
| 使用者評分 | 4.1 | 4.7 |
| 支援平台 | 網站 | 網站 |
扎根東南亞的主權高效能 AI 雲
提供隨選 GPU 執行個體與專用 H100 裸機伺服器,針對 AI 訓練、微調與高效能運算工作負載最佳化。
GreenNode Kubernetes Service 負責叢集建立與維運,讓團隊無需自建控制平面即可大規模部署容器化應用。
統一的 AI Platform 支援訓練與推論,MaaS 目錄提供可透過 API 呼叫的現成模型,AgentBase 協助代理上線正式環境。
區塊儲存、檔案儲存、物件儲存,VPC 網路與負載平衡、互連,以及託管的 PostgreSQL、MySQL、MariaDB、Redis、OpenSearch 與 Kafka。
由 PyTorch Lightning 創建團隊打造的 AI 雲端平台
可按秒啟動單卡、整機或預留叢集,機型從 T4、L4 到 A100、H100、H200、B200 以及 TPU,無需長期合約。
預裝 CUDA、PyTorch 與常用函式庫的開箱即用環境,可透過瀏覽器、本機 IDE 或終端機使用,並支援自動休眠以停止閒置花費。
在多節點 GPU 與高 CPU 機器上執行分散式訓練與大規模資料準備,可搶占執行個體最高可省約 80%。
不必重寫基礎設施程式碼,即可把檢查點變成端點或應用,並託管公開應用連結或私有模型 API,速率限制可設定。

專項更強Optimizes serverless pipelines specifically for generative media models, but lacks general-purpose PyTorch training studios.
專項更強透過標準化 API 簡化模型部署與微調,但對原始 GPU 叢集的細粒度控制較少。
專項更強Provides ultra-fast inference for open-weight foundation models, but is less suited for custom distributed model training workflows.

專項更強FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.
專項更強FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.