# Nebius vs QuickPod Nebius 记录了 1,145,711 月访问量，月度环比增长为 +10.7%，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。 | 指标 | [Nebius](https://openaitools.app/zh/tool/nebius) | [QuickPod](https://openaitools.app/zh/tool/quickpod) | | :--- | :--- | :--- | | 官网地址 | https://nebius.com | https://quickpod.io | | 分类 | AI Developer Tools, AI Models, AI API, Open Source AI Models | AI Developer Tools | | 定价模式 | 付费，定价请咨询 | 付费 | | 月访问量 | 1,145,711 | 7,171 | | 月度环比增长率 | +10.7% | -70.4% | | 主要市场 | 美国 | 印度尼西亚 | | 直接访问量 | 447,886 | 2,986 | | 评价得分 | 4.5 | 4 | | 收藏数 | 0 | 0 | | 支持平台 | 网站 | 网站 | ## 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) ## QuickPod 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. **定价与套餐:** Paid, usage-based pricing. On-demand CPU and GPU rates are published in the QuickPod console; there is no free tier advertised, and the platform claims savings up to 80% (about 60% on average) versus major cloud providers. - **GPU and CPU pod rentals:** Launch on-demand docker pods with GPU or CPU compute from one interface and scale up or down as workloads change. - **Pre-configured Jupyter:** Every pod ships with a Jupyter environment ready for TensorFlow, PyTorch or any framework you prefer. - **Global footprint:** Choose from a broad set of locations worldwide so compute sits close to your datasets and end users. - **Cost transparency:** On-demand CPU and GPU pricing is published in the console, so you can compare instance types before you launch. - **Monitoring and analytics:** Real-time analytics help you track utilisation and spend on the machines you run. **优势:** Up to 80% cheaper than major clouds on comparable GPU capacity; Jupyter and popular frameworks pre-installed, so jobs start immediately; Publishing on-demand rates in the console makes cost comparison easy; Broad global region choice for latency-sensitive or data-residency-conscious work [工具详情（Markdown）](https://openaitools.app/zh/tool/quickpod.md) ## 常见问题 ### Nebius 和 QuickPod 在月流量上如何比较？ Nebius 有 1,145,711 月访问量，而 QuickPod 有 7,171。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？ Nebius 的月度环比增长率为 +10.7%；QuickPod 为 -70.4%。 ### 价格如何比较？ 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. QuickPod: 付费。Paid, usage-based pricing. On-demand CPU and GPU rates are published in the QuickPod console; there is no free tier advertised, and the platform claims savings up to 80% (about 60% on average) versus major cloud providers. ## 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 | 面向 AI 开发者的 GPU Pod、Serverless 推理与集群云平台 | [.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 | 从全球市场按秒租用云 GPU | [.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 | 面向 AI 与数据负载的无服务器云基础设施 | [.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 | [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) | | 8 | [Lightning AI](https://openaitools.app/zh/tool/lightning-ai) | 272,562 | -12.3% | 免费增值，付费，定价请咨询 | 由 PyTorch Lightning 创建团队打造的 AI 云平台 | [.md](https://openaitools.app/zh/tool/lightning-ai.md) | | 9 | [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) | | 10 | [FluidStack](https://openaitools.app/zh/tool/fluidstack) | 154,620 | +7.3% | 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 | [.md](https://openaitools.app/zh/tool/fluidstack.md) | --- 来源：https://openaitools.app/zh/compare/nebius-vs-quickpod 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)