# AI/ML API vs Runware

AI/ML API 每月有 232,946 次造訪，月增率 -20.1%，定價模式為 Pay-as-you-go credits (free to start); enterprise custom pricing on request。Runware 每月有 402,862 次造訪，成長率 +27.1%，定價模式為付費。

| 指標 | [AI/ML API](https://openaitools.app/tw/tool/ai-ml-api) | [Runware](https://openaitools.app/tw/tool/runware) |
| :--- | :--- | :--- |
| 網站網址 | https://www.aimlapi.com | https://runware.ai |
| 分類 | AI API, AI 模型, AI 開發者工具 | AI API, AI 圖像生成器, Text to Image, AI 模型 |
| 定價模式 | Pay-as-you-go credits (free to start); enterprise custom pricing on request | 付費 |
| 每月造訪次數 | 232,946 | 402,862 |
| 月成長率 | -20.1% | +27.1% |
| 主要市場 | 美國 | 美國 |
| 直接造訪 | 64,194 | 189,796 |
| 評論分數 | 4.3 | 4.5 |
| 收藏數 | 3 | 0 |
| 支援平台 | 網站 | 網站 |

## AI/ML API

AI/ML API 是面向開發者的生成式 AI 聚合層。你不必逐家註冊模型廠商，只要使用統一介面與相容 OpenAI 的 SDK，現有指向 OPENAI_API_KEY、ANTHROPIC_API_KEY 或 GEMINI_API_KEY 的程式碼可改用單一 AIML_API_KEY，並透過更換模型名稱在不同模型間切換，無須重寫整合。目錄涵蓋對話與推理模型、程式碼模型、圖像與影片生成、語音合成與音樂、嵌入、OCR、內容審核以及圖生 3D 流程。

除了模型本身，平台還提供 1,000+ 的 MCP 工具面，涵蓋網頁搜尋、YouTube 字幕、X/Twitter 抓取、LinkedIn 職缺、Reddit 研究以及行銷與 SEO 資料，讓代理開發者把模型推理與即時外部資料結合起來。名為 Jev Router 的路由層會自動把簡單任務交給便宜快速的模型，把困難任務保留給前沿模型，官方稱可自動降低最高約 50% 的成本。計費按 token、圖像張數、影片秒數或音訊秒數計算，官方聲明不高於直接向廠商採購的價格。

此服務面向新創團隊與生產環境工程團隊，也服務企業客戶。自助帳戶可用較低起儲金額加值，依實際用量付費；較大型組織可申請客製價格、專屬伺服器、私有模型部署與更高速率上限，並配專屬客戶經理。隱私文件說明客戶輸入不會用於訓練或微調模型。

**價格與方案:** 按量付費，可用約 20 美元起加值，依 token、圖像、影片秒數或音訊秒數計費，官方聲明相較廠商直採為 0% 加成。企業版可申請客製價格、專屬伺服器、私有模型與不限速率。

- **統一多廠商介面:** 用一把 API Key 和一套 SDK 即可呼叫來自 70+ 廠商的對話、程式碼、圖像、影片、音訊、音樂、嵌入、OCR 與 3D 模型。
- **相容 OpenAI 的整合:** 把既有的 OpenAI、Anthropic 或 Gemini SDK 程式碼指向本平台，只需改模型名稱而不必重做整合。
- **Jev Router 成本優化:** 自動判斷任務難度，簡單任務走低價模型，困難任務升級到更強模型。
- **1,000+ MCP 代理工具:** 讓代理串接 Google 搜尋、YouTube 字幕、X/Twitter、Reddit、LinkedIn 職缺與 SEO/行銷資料。
- **統一帳單:** 模型呼叫與代理工具共用一個餘額計量，並依 token、圖像、影片、音訊分類提供用量回執。

**優勢:** 一把憑證、一張發票即可使用極廣的模型目錄; 幾乎無須改動即可接入現有 OpenAI 風格程式碼; MCP 工具庫帶來超越純模型的研究與資料能力; 官方聲明的零加成便於與廠商直採比價

**限制:** 請求鏈路引入第三方，平台故障會同時影響所有廠商模型; 成本可預測性需要持續監控按 token 與按秒計量; 部分最新模型的上架時間可能晚於廠商直發

[Profile (Markdown)](https://openaitools.app/tw/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.

**價格與方案:** 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.

**優勢:** 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

**限制:** 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

[Profile (Markdown)](https://openaitools.app/tw/tool/runware.md)

## 常見問題

### AI/ML API 與 Runware 的每月流量相比如何？

AI/ML API 每月有 232,946 次造訪，而 Runware 有 402,862。流量估算反映受眾規模，並非產品品質。

### 兩者的成長率相比如何？

AI/ML API 的月增率為 -20.1%；Runware 為 +27.1%。

### 價格相比如何？

AI/ML API：Pay-as-you-go credits (free to start); enterprise custom pricing on request。按量付費，可用約 20 美元起加值，依 token、圖像、影片秒數或音訊秒數計費，官方聲明相較廠商直採為 0% 加成。企業版可申請客製價格、專屬伺服器、私有模型與不限速率。 Runware：付費。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.

## 替代方案

| # | 工具名稱 | 每月造訪次數 | 月成長率 | 定價模式 | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [OpenAI 平台](https://openaitools.app/tw/tool/openai) | 234,678,639 | -9.6% | 付費 | Delivers native access to OpenAI's frontier language models and real-time APIs, but without multi-provider model aggregation. | [.md](https://openaitools.app/tw/tool/openai.md) |
| 2 | [Google AI Studio](https://openaitools.app/tw/tool/google-ai-studio) | 112,620,020 | +2% | 免費增值 | Provides direct developer access to Google's native Gemini models, but lacks the multi-vendor model aggregation of Target. | [.md](https://openaitools.app/tw/tool/google-ai-studio.md) |
| 3 | [OpenRouter](https://openaitools.app/tw/tool/openrouter-ai) | 19,941,437 | -6.2% | 付費 | 一個 API 金鑰，呼叫各大廠商數百個 AI 模型 | [.md](https://openaitools.app/tw/tool/openrouter-ai.md) |
| 4 | [RunningHub](https://openaitools.app/tw/tool/runninghub) | 3,105,554 | -28.5% | 免費增值 | 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/tw/tool/runninghub.md) |
| 5 | [fal.ai](https://openaitools.app/tw/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | 提供類似的開發者優先雲端平台以進行超快速生成式多媒體推理，但定價級別有所不同。 | [.md](https://openaitools.app/tw/tool/fal-ai.md) |
| 6 | [Together AI](https://openaitools.app/tw/tool/together-ai) | 1,645,930 | +64.9% | 免費增值、付費 | 更專注於開源 LLM 代管與專用叢集，但較不適合即時圖片生成。 | [.md](https://openaitools.app/tw/tool/together-ai.md) |
| 7 | [Replicate AI](https://openaitools.app/tw/tool/replicate-ai) | 904,038 | -8.4% | 付費 | 提供相近的無伺服器模型部署與微調，但具備更廣泛的通用機器學習生態系統。 | [.md](https://openaitools.app/tw/tool/replicate-ai.md) |
| 8 | [Atlas Cloud](https://openaitools.app/tw/tool/atlas-cloud) | 777,031 | -16.4% | 付費 | 提供生成式媒體模型的統一存取，但缺乏 Runware 對原始推論速度的專門關注。 | [.md](https://openaitools.app/tw/tool/atlas-cloud.md) |
| 9 | [CometAPI](https://openaitools.app/tw/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/tw/tool/cometapi.md) |
| 10 | [DeepInfra](https://openaitools.app/tw/tool/deep-infra) | 457,810 | -8.9% | 付費 | 擅長低成本的開源權重模型推論，但針對複雜圖片生成管線的專門工具較少。 | [.md](https://openaitools.app/tw/tool/deep-infra.md) |

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來源：https://openaitools.app/tw/compare/ai-ml-api-vs-runware

More Markdown: [分類](https://openaitools.app/tw/categories.md) · [流量排名](https://openaitools.app/tw/rankings.md) · [llms.txt](https://openaitools.app/tw/llms.txt)