Nebius: 提供专属的 NVIDIA GPU 集群和托管云基础设施，直接在企业级训练工作负载上展开竞争。 FluidStack 记录了 154,620 月访问量，月度环比增长为 +7.3%，定价为付费，定价请咨询。Nebius 记录了 1,145,711 月访问量，增长率为 +10.7%，定价为付费，定价请咨询。
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.
Nebius is an AI-focused cloud platform that gives teams non-virtualized NVIDIA GPU clusters, managed MLOps tooling, and a serverless inference layer so they can move from experiment to production on one stack.
| 维度 / 指标 | | |
|---|---|---|
| 官方域名 | fluidstack.io | nebius.com |
| 定价模式 | 付费，定价请咨询 | 付费，定价请咨询 |
| 月访问量 | 15.46万 (154,620) | 114.57万 (1,145,711) |
| 月度环比流量变化 | +1.05万 (+7.3%) | +11.08万 (+10.7%) |
| 主要市场与份额 | 🇺🇸 美国 (95.7%) | 🇺🇸 美国 (46.8%) |
| 直接访问 / 月 | 4.79万 | 44.79万 |
| 用户评分 | 4.4 | 4.5 |
| 支持的平台 | 网站 | 网站 |
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.
FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.
Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
Nebius is an AI-focused cloud platform that gives teams non-virtualized NVIDIA GPU clusters, managed MLOps tooling, and a serverless inference layer so they can move from experiment to production on one stack.
Bare-metal access to NVIDIA GB300, B300, GB200, B200, H200, H100, RTX PRO 6000, and L40S GPUs connected over InfiniBand for training and inference at scale.
A managed inference service for running popular open and frontier models through an API, so applications can add LLM capabilities without owning GPUs.
Built-in Kubernetes, Soperator for Slurm jobs, PostgreSQL, and MLflow give teams a ready-made environment for orchestration, tracking, and experiments.
Choose on-demand, preemptible, or live market-driven spot capacity, or commit to reserved clusters for discounts on long-running workloads.
专项更强Tailored specifically for high-throughput generative media inference pipelines, whereas Nebius targets general GPU compute infrastructure.
专项更强Tailored specifically for high-throughput generative media inference pipelines, whereas Nebius targets general GPU compute infrastructure.
提供灵活按需的 GPU 租用与无服务器节点，但比起开箱即用的企业级集群，更专注于灵活的开发者实例。
为开源模型提供强大的无服务器推理 API 与 GPU 集群，但对底层裸机控制的侧重较少。
提供价格较低的 P2P GPU 租赁市场，不过与托管基础设施相比，硬件可靠性不太稳定。
专项更强能在无服务器容器中轻松运行 Python 工作负载与模型推理，但缺乏裸机集群管理功能。
专项更强能在无服务器容器中轻松运行 Python 工作负载与模型推理，但缺乏裸机集群管理功能。
免费 / 开源编排全球闲置消费级 GPU 的分布式 GPU 云
专项更强采用独家晶圆级处理器以实现极端的训练速度，有别于标准的 NVIDIA GPU 集群设置。
专项更强Provides exceptionally cheap serverless inference for open models via API, but does not offer raw bare-metal GPU rentals.
专项更强Provides interactive development studios and on-demand GPUs for training, but focuses more on PyTorch workflows than raw infrastructure.
专项更强Provides interactive development studios and on-demand GPUs for training, but focuses more on PyTorch workflows than raw infrastructure.
专项更强Combines model APIs and serverless GPU jobs, but lacks the enterprise-grade bare-metal infrastructure orchestration of Nebius.
专项更强Built on Ray for distributed model training and scaling workloads, but relies on underlying cloud providers rather than owned GPUs.
专项更强Built on Ray for distributed model training and scaling workloads, but relies on underlying cloud providers rather than owned GPUs.
面向训练与推理工作负载的私有 AI 云
