# FluidStack vs Nebius

FluidStack 每月有 154,620 次造訪，月增率 +7.3%，定價模式為付費、需聯絡報價。Nebius 每月有 1,145,711 次造訪，成長率 +10.7%，定價模式為付費、需聯絡報價。

| 指標 | [FluidStack](https://openaitools.app/tw/tool/fluidstack) | [Nebius](https://openaitools.app/tw/tool/nebius) |
| :--- | :--- | :--- |
| 網站網址 | https://fluidstack.io | https://nebius.com |
| 分類 | AI 開發者工具, AI 模型, Large Language Models (LLMs) | AI 開發者工具, AI 模型, AI API, 開源 AI 模型 |
| 定價模式 | 付費、需聯絡報價 | 付費、需聯絡報價 |
| 每月造訪次數 | 154,620 | 1,145,711 |
| 月成長率 | +7.3% | +10.7% |
| 主要市場 | 美國 | 美國 |
| 直接造訪 | 47,869 | 447,886 |
| 評論分數 | 4.4 | 4.5 |
| 收藏數 | 1 | 0 |
| 支援平台 | 網站 | 網站 |

## 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.

**價格與方案:** 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.

**優勢:** 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

**限制:** 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

[Profile (Markdown)](https://openaitools.app/tw/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.

**價格與方案:** 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.

**優勢:** 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

**限制:** 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

[Profile (Markdown)](https://openaitools.app/tw/tool/nebius.md)

## 常見問題

### FluidStack 與 Nebius 的每月流量相比如何？

FluidStack 每月有 154,620 次造訪，而 Nebius 有 1,145,711。流量估算反映受眾規模，並非產品品質。

### 兩者的成長率相比如何？

FluidStack 的月增率為 +7.3%；Nebius 為 +10.7%。

### 價格相比如何？

FluidStack：付費、需聯絡報價。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：付費、需聯絡報價。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.

## 替代方案

| # | 工具名稱 | 每月造訪次數 | 月成長率 | 定價模式 | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [fal.ai](https://openaitools.app/tw/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/tw/tool/fal-ai.md) |
| 2 | [RunPod](https://openaitools.app/tw/tool/runpod) | 2,881,043 | +5.9% | 付費 | 提供靈活隨需的 GPU 租用與無伺服器節點，但比起開箱即用的企業級叢集，更專注於靈活的開發者實例。 | [.md](https://openaitools.app/tw/tool/runpod.md) |
| 3 | [Together AI](https://openaitools.app/tw/tool/together-ai) | 1,645,930 | +64.9% | 免費增值、付費 | 為開源模型提供強大的無伺服器推論 API 與 GPU 叢集，但對底層裸機控制的著墨較少。 | [.md](https://openaitools.app/tw/tool/together-ai.md) |
| 4 | [Vast.ai](https://openaitools.app/tw/tool/vast-ai) | 1,257,554 | +2.8% | 付費 | 提供價格較低的 P2P GPU 租賃市場，不過與託管基礎設施相比，硬體可靠性較不穩定。 | [.md](https://openaitools.app/tw/tool/vast-ai.md) |
| 5 | [Modal](https://openaitools.app/tw/tool/modal-com) | 1,196,021 | +30.2% | 免費增值、需聯絡報價 | 能在無伺服器容器中輕鬆執行 Python 工作負載與模型推論，但缺乏裸機叢集管理功能。 | [.md](https://openaitools.app/tw/tool/modal-com.md) |
| 6 | [Salad](https://openaitools.app/tw/tool/salad-gpu-cloud) | 713,519 | +10.4% | 免費試用、付費、需聯絡報價 | 編排全球閒置消費級 GPU 的分散式 GPU 雲 | [.md](https://openaitools.app/tw/tool/salad-gpu-cloud.md) |
| 7 | [Cerebras](https://openaitools.app/tw/tool/cerebras) | 701,013 | -12.6% | 需聯絡報價 | 採用獨家晶圓級處理器以實現極端訓練速度，有別於標準的 NVIDIA GPU 叢集設置。 | [.md](https://openaitools.app/tw/tool/cerebras.md) |
| 8 | [DeepInfra](https://openaitools.app/tw/tool/deep-infra) | 457,810 | -8.9% | 付費 | Provides exceptionally cheap serverless inference for open models via API, but does not offer raw bare-metal GPU rentals. | [.md](https://openaitools.app/tw/tool/deep-infra.md) |
| 9 | [Lightning AI](https://openaitools.app/tw/tool/lightning-ai) | 272,562 | -12.3% | 免費增值、付費、需聯絡報價 | Provides interactive development studios and on-demand GPUs for training, but focuses more on PyTorch workflows than raw infrastructure. | [.md](https://openaitools.app/tw/tool/lightning-ai.md) |
| 10 | [Novita AI](https://openaitools.app/tw/tool/novita-ai) | 271,371 | -10.4% | 付費 | Combines model APIs and serverless GPU jobs, but lacks the enterprise-grade bare-metal infrastructure orchestration of Nebius. | [.md](https://openaitools.app/tw/tool/novita-ai.md) |

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來源：https://openaitools.app/tw/compare/fluidstack-vs-nebius

More Markdown: [分類](https://openaitools.app/tw/categories.md) · [流量排名](https://openaitools.app/tw/rankings.md) · [llms.txt](https://openaitools.app/tw/llms.txt)