Modal 记录了 1,196,021 月访问量，月度环比增长为 +30.2%，定价为免费增值，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。
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 | modal.com | quickpod.io |
| 定价模式 | 免费增值，定价请咨询 | 付费 |
| 月访问量 | 119.6万 (1,196,021) | 7171 (7,171) |
| 月度环比流量变化 | +27.72万 (+30.2%) | -1.71万 (-70.4%) |
| 主要市场与份额 | 🇺🇸 美国 (43.9%) | 🇮🇩 印度尼西亚 (100%) |
| 直接访问 / 月 | 84.56万 | 2986 |
| 用户评分 | 4.8 | 4 |
| 支持的平台 | 网站 | 网站 |
面向 AI 与数据负载的无服务器云基础设施
直接写 Python，挂载 GPU 或容器，部署成随流量伸缩、空闲时缩容到零的 HTTPS 端点。
为编码智能体、强化学习 rollout 和不可信代码提供隔离安全环境，启动低于一秒，可支持百万级并发沙箱。
在弹性单机或多机 GPU 算力上运行微调、LoRA、全量训练和强化学习，无需等待配额审批。
通过兼容 OpenAI 的端点服务大语言模型以及图像、视频、音频模型，也可以自带推理栈，由 Modal 负责底层基础设施。
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.
专项更强专为生成式多媒体模型优化的超快速无服务器运行环境，而非通用的 Python 代码。
从全球市场按秒租用云 GPU
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.
通过 Cog 可以更轻松地打包模型，但不如 Modal 提供那么多样的无服务器 Python 容器运行方式。
免费 / 开源编排全球闲置消费级 GPU 的分布式 GPU 云
免费 / 开源由 PyTorch Lightning 创建团队打造的 AI 云平台
专项更强Combines ready-to-use model APIs and serverless GPU jobs, with simpler API consumption than custom Modal apps.
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 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.
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。
