QuickPod 记录了 7,171 月访问量，月度环比增长为 -70.4%，定价为付费。Salad 记录了 713,519 月访问量，增长率为 +10.4%，定价为免费试用，付费，定价请咨询。
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 | quickpod.io | salad.com |
| 定价模式 | 付费 | 免费试用，付费，定价请咨询 |
| 月访问量 | 7171 (7,171) | 71.35万 (713,519) |
| 月度环比流量变化 | -1.71万 (-70.4%) | +6.75万 (+10.4%) |
| 主要市场与份额 | 🇮🇩 印度尼西亚 (100%) | 🇺🇸 美国 (40.9%) |
| 直接访问 / 月 | 2986 | 44.09万 |
| 用户评分 | 4 | 4.3 |
| 支持的平台 | 网站 | 网站 |
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.
编排全球闲置消费级 GPU 的分布式 GPU 云
在数千个分布式 GPU 节点上调度、监控并重新分配 Docker/OCI 工作负载，节点消失时自动故障转移。
按需访问覆盖 190 多个国家的闲置消费级 GPU 分布式算力池，优先定价约从每小时 0.015 美元起。
面向开源权重模型的托管 token 端点，按 token 计费，你的数据不会被用于训练。
在组织内部运行同一套编排栈，把闲置工作站 GPU 汇聚成内部兼容 OpenAI 的服务。
专项更强专门提供开源模型的托管式无服务器推理 API，而非单纯租赁 GPU 基础设施。
提供价格更低廉的广泛 P2P GPU 市场，但需要较多手动配置。
专项更强为 AI 流水线提供轻松的 Python 无服务器执行，但专注于 Function-as-a-Service 而非裸机虚拟机。
专项更强为 AI 流水线提供轻松的 Python 无服务器执行，但专注于 Function-as-a-Service 而非裸机虚拟机。
提供企业级 NVIDIA GPU 集群与托管式 ML 工具，但专业价格定位较高。
专项更强Offers extremely cheap serverless model hosting via API, but does not provide raw containerized GPU instances.
免费 / 开源由 PyTorch Lightning 创建团队打造的 AI 云平台
Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.
Focuses on large-scale enterprise GPU clusters for training, rather than lightweight consumer container workloads.
Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.
Features second-billed persistent SSH GPU instances, but lacks a distributed consumer hardware backbone.
代理优先的 GPU 云：在终端或 API 中按秒租用 NVIDIA 算力
专项更强Scales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.
专项更强Scales distributed Ray workloads effortlessly across clusters, but is tailored for heavy data engineering and training.
