# FluidStack vs Nebius

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。

| 指标 | [FluidStack](https://openaitools.app/zh/tool/fluidstack) | [Nebius](https://openaitools.app/zh/tool/nebius) |
| :--- | :--- | :--- |
| 官网地址 | https://fluidstack.io | https://nebius.com |
| 分类 | AI Developer Tools, AI Models, Large Language Models (LLMs) | AI Developer Tools, AI Models, AI API, Open Source AI Models |
| 定价模式 | 付费，定价请咨询 | 付费，定价请咨询 |
| 月访问量 | 154,620 | 1,145,711 |
| 月度环比增长率 | +7.3% | +10.7% |
| 主要市场 | 美国 | 美国 |
| 直接访问量 | 47,869 | 447,886 |
| 评价得分 | 4.4 | 4.5 |
| 收藏数 | 1 | 0 |
| 支持平台 | 网站 | 网站 |

## FluidStack

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.

**定价与套餐:** Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing.

- **Datacenter-scale compute built in-house:** 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.
- **GPU clusters for training and inference:** Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
- **Power and cooling engineered together:** The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
- **Managed operations and reliability:** Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
- **US-built and onshored supply chain:** Data centers are built in the United States with onshored manufacturing of compute and power infrastructure, a deliberate supply-chain and sovereignty choice.

**优势:** Purpose-built AI infrastructure rather than generic cloud resale; Power, cooling and data center design handled in-house, which matters at scale; Managed provisioning and operations for large training and inference clusters; Explicit positioning on US-built, onshored infrastructure

**局限:** No published self-serve pricing or instant sign-up; access requires a sales conversation; Enterprise-scale focus means very small individual workloads may not be a fit; Capacity is concentrated in US locations, which may matter for latency-sensitive or data-residency-bound teams

[工具详情（Markdown）](https://openaitools.app/zh/tool/fluidstack.md)

## Nebius

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.

**定价与套餐:** Usage-based pricing published on the site. On-demand GPU instances range from roughly $1.55/GPU-hour for L40S up to about $9.50/GPU-hour for HGX B300, with preemptible and live spot options starting around $0.79/GPU-hour. CPU-only instances start near $0.06/cpu-hour, managed Kubernetes and networking are free, and large-scale clusters or commitments are quoted through sales.

- **Non-virtualized GPU clusters:** 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.
- **Nebius Token Factory:** A managed inference service for running popular open and frontier models through an API, so applications can add LLM capabilities without owning GPUs.
- **Managed MLOps services:** Built-in Kubernetes, Soperator for Slurm jobs, PostgreSQL, and MLflow give teams a ready-made environment for orchestration, tracking, and experiments.
- **Flexible consumption and spot pricing:** Choose on-demand, preemptible, or live market-driven spot capacity, or commit to reserved clusters for discounts on long-running workloads.
- **Scalable AI storage:** Shared filesystems, WEKA, block volumes, and tiered object storage sized for multi-hundred-terabyte training datasets.

**优势:** Transparent, publicly listed per-hour GPU and storage pricing; Broad NVIDIA lineup from L40S up to GB300 NVL72; Free Kubernetes management, networking egress, and public IPs; Integrated MLOps tooling including MLflow, Slurm via Soperator, and PostgreSQL

**局限:** Top-end clusters like GB300 and GB200 are quote-only, not self-serve; Spot and preemptible capacity is interruptible and prices move with demand; Requires meaningful ML infrastructure knowledge to get the most out of it

[工具详情（Markdown）](https://openaitools.app/zh/tool/nebius.md)

## 常见问题

### FluidStack 和 Nebius 在月流量上如何比较？

FluidStack 有 154,620 月访问量，而 Nebius 有 1,145,711。流量估算描述的是受众规模，而非产品质量。

### 它们的增长率如何比较？

FluidStack 的月度环比增长率为 +7.3%；Nebius 为 +10.7%。

### 价格如何比较？

FluidStack: 付费，定价请咨询。Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing. Nebius: 付费，定价请咨询。Usage-based pricing published on the site. On-demand GPU instances range from roughly $1.55/GPU-hour for L40S up to about $9.50/GPU-hour for HGX B300, with preemptible and live spot options starting around $0.79/GPU-hour. CPU-only instances start near $0.06/cpu-hour, managed Kubernetes and networking are free, and large-scale clusters or commitments are quoted through sales.

## 替代工具

| # | 工具名称 | 月访问量 | 月度环比增长率 | 定价模式 | 简介 | 工具详情（Markdown） |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [fal.ai](https://openaitools.app/zh/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Tailored specifically for high-throughput generative media inference pipelines, whereas Nebius targets general GPU compute infrastructure. | [.md](https://openaitools.app/zh/tool/fal-ai.md) |
| 2 | [RunPod](https://openaitools.app/zh/tool/runpod) | 2,881,043 | +5.9% | 付费 | 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。 | [.md](https://openaitools.app/zh/tool/runpod.md) |
| 3 | [Together AI](https://openaitools.app/zh/tool/together-ai) | 1,645,930 | +64.9% | 免费增值，付费 | 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。 | [.md](https://openaitools.app/zh/tool/together-ai.md) |
| 4 | [Vast.ai](https://openaitools.app/zh/tool/vast-ai) | 1,257,554 | +2.8% | 付费 | 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。 | [.md](https://openaitools.app/zh/tool/vast-ai.md) |
| 5 | [Modal](https://openaitools.app/zh/tool/modal-com) | 1,196,021 | +30.2% | 免费增值，定价请咨询 | 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。 | [.md](https://openaitools.app/zh/tool/modal-com.md) |
| 6 | [Salad](https://openaitools.app/zh/tool/salad-gpu-cloud) | 713,519 | +10.4% | 免费试用，付费，定价请咨询 | 编排全球闲置消费级 GPU 的分布式 GPU 云 | [.md](https://openaitools.app/zh/tool/salad-gpu-cloud.md) |
| 7 | [Cerebras](https://openaitools.app/zh/tool/cerebras) | 701,013 | -12.6% | 定价请咨询 | 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。 | [.md](https://openaitools.app/zh/tool/cerebras.md) |
| 8 | [DeepInfra](https://openaitools.app/zh/tool/deep-infra) | 457,810 | -8.9% | 付费 | Provides exceptionally cheap serverless inference for open models via API, but does not offer raw bare-metal GPU rentals. | [.md](https://openaitools.app/zh/tool/deep-infra.md) |
| 9 | [Lightning AI](https://openaitools.app/zh/tool/lightning-ai) | 272,562 | -12.3% | 免费增值，付费，定价请咨询 | Provides interactive development studios and on-demand GPUs for training, but focuses more on PyTorch workflows than raw infrastructure. | [.md](https://openaitools.app/zh/tool/lightning-ai.md) |
| 10 | [Novita AI](https://openaitools.app/zh/tool/novita-ai) | 271,371 | -10.4% | 付费 | Combines model APIs and serverless GPU jobs, but lacks the enterprise-grade bare-metal infrastructure orchestration of Nebius. | [.md](https://openaitools.app/zh/tool/novita-ai.md) |

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来源：https://openaitools.app/zh/compare/fluidstack-vs-nebius

更多 Markdown 页面: [分类](https://openaitools.app/zh/categories.md) · [流量排名](https://openaitools.app/zh/rankings.md) · [llms.txt](https://openaitools.app/zh/llms.txt)