RunningHub 记录了 3,105,554 月访问量,月度环比增长为 -28.5%,定价为免费增值。Runware 记录了 402,862 月访问量,增长率为 +27.1%,定价为付费。

RunningHub is a cloud platform for running ComfyUI workflows online, building AI apps, and generating images and videos with hosted models and APIs.

Runware is an AI inference platform that exposes an enormous model catalog — images, video, audio, LLMs and 3D — through a single API endpoint, alongside serverless GPU compute and reserved capacity running on modular data centers the company designs and operates itself. It is aimed at developers and product teams who want to ship generative features without managing infrastructure.
| 维度 / 指标 | ![]() | ![]() |
|---|---|---|
| 官方域名 | runninghub.ai | runware.ai |
| 定价模式 | 免费增值 | 付费 |
| 月访问量 | 310.56万 (3,105,554) | 40.29万 (402,862) |
| 月度环比流量变化 | -123.77万 (-28.5%) | +8.58万 (+27.1%) |
| 主要市场与份额 | 🇨🇳 中国 (52.7%) | 🇺🇸 美国 (27.3%) |
| 直接访问 / 月 | 229.72万 | 18.98万 |
| 用户评分 | 4.4 | 4.5 |
| 支持的平台 | 网站 | 网站 |

RunningHub is a cloud platform for running ComfyUI workflows online, building AI apps, and generating images and videos with hosted models and APIs.
Run, import, and share ComfyUI workflows in the cloud without local GPU hardware.
Publish a workflow as a single-click AI app that anyone can run with simple inputs.
Use hosted image and video models, including self-developed upscaling and enhancement tools, from one dashboard.
Integrate generation into your product via workflow, model, LLM, and app APIs.

Runware is an AI inference platform that exposes an enormous model catalog — images, video, audio, LLMs and 3D — through a single API endpoint, alongside serverless GPU compute and reserved capacity running on modular data centers the company designs and operates itself. It is aimed at developers and product teams who want to ship generative features without managing infrastructure.
Image, video, audio, LLM and 3D tasks all POST to a single endpoint as an array, so mixed-modality batches can travel in one request with shared auth and billing.
Browse hosted, partner and community models through one addressing scheme, control parameters such as stacked LoRAs and swapped VAEs on open models, and add your own uploads.
Bring your own container and weights to serverless GPUs billed by the second that scale to zero when idle, or commit to reserved capacity and bare-metal clusters for a lower per-hour rate.
Purpose-built modular data centers plus an orchestration layer that keeps weights preloaded across regions and routes requests to pods that already hold the model in memory.
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