# AI/ML API vs Runware

AI/ML API 记录了 232,946 月访问量，月度环比增长为 -20.1%，定价为 Pay-as-you-go credits (free to start); enterprise custom pricing on request。Runware 记录了 402,862 月访问量，增长率为 +27.1%，定价为付费。

| 指标 | [AI/ML API](https://openaitools.app/zh/tool/ai-ml-api) | [Runware](https://openaitools.app/zh/tool/runware) |
| :--- | :--- | :--- |
| 官网地址 | https://www.aimlapi.com | https://runware.ai |
| 分类 | AI API, AI Models, AI Developer Tools | AI API, AI Image Generator, Text to Image, AI Models |
| 定价模式 | Pay-as-you-go credits (free to start); enterprise custom pricing on request | 付费 |
| 月访问量 | 232,946 | 402,862 |
| 月度环比增长率 | -20.1% | +27.1% |
| 主要市场 | 美国 | 美国 |
| 直接访问量 | 64,194 | 189,796 |
| 评价得分 | 4.3 | 4.5 |
| 收藏数 | 3 | 0 |
| 支持平台 | 网站 | 网站 |

## AI/ML API

AI/ML API 是面向开发者的生成式 AI 聚合层。你无需逐家注册模型厂商，只需使用统一接口与兼容 OpenAI 的 SDK，现有指向 OPENAI_API_KEY、ANTHROPIC_API_KEY 或 GEMINI_API_KEY 的代码可以改用单一 AIML_API_KEY，并通过更换模型名称在不同模型间切换，无需重写集成。目录涵盖对话与推理模型、代码模型、图像与视频生成、语音合成与音乐、嵌入、OCR、内容审核以及图生 3D 流程。

除模型本身外，平台还提供 1,000+ 的 MCP 工具面，覆盖网页搜索、YouTube 字幕、X/Twitter 抓取、LinkedIn 招聘、Reddit 调研以及营销与 SEO 数据，让智能体开发者把模型推理与实时外部数据结合起来。名为 Jev Router 的路由层会自动把简单任务交给便宜快速的模型，把困难任务保留给前沿模型，官方称可自动降低最高约 50% 的成本。计费按 token、图像张数、视频秒数或音频秒数计量，官方声明不高于直接向厂商采购的价格。

该服务面向创业公司与生产环境工程团队，也服务企业客户。自助账户可用较低起充金额充值，按实际用量付费；较大组织可申请定制价格、专属服务器、私有模型部署与更高限速，并配备专属客户经理。隐私文档说明客户输入不会用于训练或微调模型。

**定价与套餐:** 按量付费，可用约 20 美元起充值，按 token、图像、视频秒数或音频秒数计费，官方声明相比厂商直采为 0% 加价。企业版可申请定制价格、专属服务器、私有模型与不限速率。

- **统一多厂商接口:** 用一把 API Key 和一套 SDK 即可调用来自 70+ 厂商的对话、代码、图像、视频、音频、音乐、嵌入、OCR 与 3D 模型。
- **兼容 OpenAI 的集成:** 把已有的 OpenAI、Anthropic 或 Gemini SDK 代码指向本平台，只需改模型名而不必重做集成。
- **Jev Router 成本优化:** 自动判断任务难度，简单任务走低价模型，困难任务升级到更强模型。
- **1,000+ MCP 智能体工具:** 让智能体接入 Google 搜索、YouTube 字幕、X/Twitter、Reddit、LinkedIn 招聘与 SEO/营销数据。
- **统一账单:** 模型调用与智能体工具共用一个余额计量，并按 token、图像、视频、音频分类提供用量回执。

**优势:** 一把凭证、一张发票即可使用极广的模型目录; 几乎无需改动即可接入现有 OpenAI 风格代码; MCP 工具库带来超越纯模型的研究与数据能力; 官方声明的零加价便于与厂商直采比价

**局限:** 请求链路引入第三方，平台故障会同时影响所有厂商模型; 成本可预测性需要持续监控按 token 与按秒计量; 部分最新模型的上架时间可能晚于厂商直发

[工具详情（Markdown）](https://openaitools.app/zh/tool/ai-ml-api.md)

## Runware

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.

**定价与套餐:** Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales.

- **One API for every modality:** 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.
- **400K+ model catalog:** 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.
- **Serverless and reserved GPU compute:** 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.
- **Sonic Pods and the Sonic Inference Engine:** 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.
- **Developer tooling and agent integrations:** A hosted MCP server, CLI, skill files, playground, model schemas and llms.txt let you wire Runware into Claude Code, Cursor, Codex or any MCP-capable client with minimal setup.
- **Enterprise-grade trust and compliance:** SOC 2, ISO 27001 and GDPR compliance, EU and US data residency, SSO/SAML, configurable MFA, a strict no-training-on-customer-data policy and optional Zero Data Retention.

**优势:** Unusually broad catalog — hundreds of thousands of models behind one consistent endpoint and API key; Aggressive published pricing, with claims of up to 10x lower cost per generation than market rates; Both managed inference and raw compute in one platform, so you can migrate from API calls to your own containers without changing vendors; Real infrastructure differentiation through self-designed modular data centers rather than reselling someone else's capacity

**局限:** The breadth of the catalog and the mix of hosted, partner and community models can be overwhelming when choosing a model; Only a subset of models (currently around 300+) has published pricing on the rate sheet, so some community models require checking the playground for cost; LLM billing splits input, output and cache-read token dimensions, adding complexity to cost forecasting; Bare-metal and high-volume reserved capacity are sales-gated rather than self-serve

[工具详情（Markdown）](https://openaitools.app/zh/tool/runware.md)

## 常见问题

### AI/ML API 和 Runware 在月流量上如何比较？

AI/ML API 有 232,946 月访问量，而 Runware 有 402,862。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？

AI/ML API 的月度环比增长率为 -20.1%；Runware 为 +27.1%。

### 价格如何比较？

AI/ML API: Pay-as-you-go credits (free to start); enterprise custom pricing on request。按量付费，可用约 20 美元起充值，按 token、图像、视频秒数或音频秒数计费，官方声明相比厂商直采为 0% 加价。企业版可申请定制价格、专属服务器、私有模型与不限速率。 Runware: 付费。Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales.

## 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 | [OpenAI 平台](https://openaitools.app/zh/tool/openai) | 234,678,639 | -9.6% | 付费 | Delivers native access to OpenAI's frontier language models and real-time APIs, but without multi-provider model aggregation. | [.md](https://openaitools.app/zh/tool/openai.md) |
| 2 | [Google AI Studio](https://openaitools.app/zh/tool/google-ai-studio) | 112,620,020 | +2% | 免费增值 | Provides direct developer access to Google's native Gemini models, but lacks the multi-vendor model aggregation of Target. | [.md](https://openaitools.app/zh/tool/google-ai-studio.md) |
| 3 | [OpenRouter](https://openaitools.app/zh/tool/openrouter-ai) | 19,941,437 | -6.2% | 付费 | 一个 API 密钥，调用各大厂商数百个 AI 模型 | [.md](https://openaitools.app/zh/tool/openrouter-ai.md) |
| 4 | [RunningHub](https://openaitools.app/zh/tool/runninghub) | 3,105,554 | -28.5% | 免费增值 | RunningHub is a cloud platform for running ComfyUI workflows online, building AI apps, and generating images and videos with hosted models and APIs. | [.md](https://openaitools.app/zh/tool/runninghub.md) |
| 5 | [fal.ai](https://openaitools.app/zh/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | 提供类似的开发者优先云端平台以进行超快速生成式多媒体推理，但定价级别有所不同。},{de: | [.md](https://openaitools.app/zh/tool/fal-ai.md) |
| 6 | [Together AI](https://openaitools.app/zh/tool/together-ai) | 1,645,930 | +64.9% | 免费增值，付费 | 更专注于开源 LLM 托管与专用集群，但对即时图片生成的针对性稍弱。 | [.md](https://openaitools.app/zh/tool/together-ai.md) |
| 7 | [Replicate AI](https://openaitools.app/zh/tool/replicate-ai) | 904,038 | -8.4% | 付费 | 提供相近的无服务器模型部署与微调，但具备更广泛的通用机器学习生态系统。},{de: | [.md](https://openaitools.app/zh/tool/replicate-ai.md) |
| 8 | [Atlas Cloud](https://openaitools.app/zh/tool/atlas-cloud) | 777,031 | -16.4% | 付费 | 提供了生成式媒体模型的统一访问，但缺乏 Runware 对原始推理速度的专注。 | [.md](https://openaitools.app/zh/tool/atlas-cloud.md) |
| 9 | [CometAPI](https://openaitools.app/zh/tool/cometapi) | 602,966 | +49.7% | Pay-as-you-go (credits) | Consolidates hundreds of large AI models under a single OpenAI-compatible endpoint, offering competitive multi-model routing and billing. | [.md](https://openaitools.app/zh/tool/cometapi.md) |
| 10 | [DeepInfra](https://openaitools.app/zh/tool/deep-infra) | 457,810 | -8.9% | 付费 | 擅长低成本的开源权重模型推理，但针对复杂图片生成管线的专门工具较少。 | [.md](https://openaitools.app/zh/tool/deep-infra.md) |

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来源：https://openaitools.app/zh/compare/ai-ml-api-vs-runware

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)