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。QuickPod 记录了 7,171 月访问量，增长率为 -70.4%，定价为付费。
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.
QuickPod rents on-demand GPU and CPU docker pods through one console, pre-configured with Jupyter for TensorFlow, PyTorch or any framework, at a fraction of major cloud prices.
| 维度 / 指标 | | |
|---|---|---|
| 官方域名 | fluidstack.io | quickpod.io |
| 定价模式 | 付费，定价请咨询 | 付费 |
| 月访问量 | 15.46万 (154,620) | 7171 (7,171) |
| 月度环比流量变化 | +1.05万 (+7.3%) | -1.71万 (-70.4%) |
| 主要市场与份额 | 🇺🇸 美国 (95.7%) | 🇮🇩 印度尼西亚 (100%) |
| 直接访问 / 月 | 4.79万 | 2986 |
| 用户评分 | 4.4 | 4 |
| 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.
QuickPod rents on-demand GPU and CPU docker pods through one console, pre-configured with Jupyter for TensorFlow, PyTorch or any framework, at a fraction of major cloud prices.
Launch on-demand docker pods with GPU or CPU compute from one interface and scale up or down as workloads change.
Every pod ships with a Jupyter environment ready for TensorFlow, PyTorch or any framework you prefer.
Choose from a broad set of locations worldwide so compute sits close to your datasets and end users.
On-demand CPU and GPU pricing is published in the console, so you can compare instance types before you launch.
专项更强Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure.
专项更强Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure.
专项更强专注于优化的无服务器推理 API 和托管模型托管，而不是单纯的裸集群租赁。
从全球市场按秒租用云 GPU
免费 / 开源面向 AI 与数据负载的无服务器云基础设施
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.
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.
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Specializes in cost-effective serverless API inference for open-weights models instead of raw infrastructure rentals.
免费 / 开源由 PyTorch Lightning 创建团队打造的 AI 云平台
低成本云 GPU：面向 AI 工作负载的按分钟实例与按秒计费沙箱。
低成本云 GPU：面向 AI 工作负载的按分钟实例与按秒计费沙箱。
代理优先的 GPU 云：在终端或 API 中按秒租用 NVIDIA 算力
