# MuAPI vs Runware

MuAPI 每月有 412,788 次造訪，月增率 +13.7%，定價模式為免費增值。Runware 每月有 402,862 次造訪，成長率 +27.1%，定價模式為付費。

| 指標 | [MuAPI](https://openaitools.app/tw/tool/muapi) | [Runware](https://openaitools.app/tw/tool/runware) |
| :--- | :--- | :--- |
| 網站網址 | https://muapi.ai | https://runware.ai |
| 分類 | AI API, AI 圖像生成器, AI Video Generator, Text to Image | AI API, AI 圖像生成器, Text to Image, AI 模型 |
| 定價模式 | 免費增值 | 付費 |
| 每月造訪次數 | 412,788 | 402,862 |
| 月成長率 | +13.7% | +27.1% |
| 主要市場 | 印度 | 美國 |
| 直接造訪 | 227,351 | 189,796 |
| 評論分數 | 4.3 | 4.5 |
| 收藏數 | 0 | 0 |
| 支援平台 | 網站 | 網站 |

## MuAPI

許多打造生成式 AI 功能的團隊最後都得同時管理多家供應商，每家都有自己的金鑰、額度制度與 API 形式。MuAPI 把這些整合成單一介接：一個端點將請求導向指定模型並回傳一致格式的回應。它涵蓋影像生成與編輯、從文字或靜態圖片生成影片，以及音訊與音樂生成，因此產品只要指向另一個模型就能增加能力，而不必導入新供應商。

平台明顯以開發者為對象。文件、API 金鑰、接近 SDK 的工作流程、CLI 與供代理工具使用的 MCP 伺服器，搭配可快速測試提示詞的互動式工作室。排名與模型排行榜協助判斷某個模型是否值得其價格，工作流程與代理功能則可串接模型，例如先生成靜態圖再於下一步轉成動畫。

計費採用以 token 與任務為單位的點數制，而非座位制；官方以比直接呼叫供應商更低的成本作為定位，並表示失敗任務不計費。新模型推出速度很快，請把模型目錄視為持續變動的清單，並在編列正式預算前確認定價頁面。

**價格與方案:** 採用量計費（pay-as-you-go）的點數制，並提供實驗用免費額度；官方標榜所有模型共用一個餘額、失敗任務不計費。各模型實際費率變動頻繁，請以定價頁面為準。

- **一個 API 取用數百個媒體模型:** 以同一套驗證與計費使用文生圖、圖生影、文生影、放大、去背、換臉與對嘴功能。
- **依模型進行多供應商路由:** 針對特定模型選擇最便宜或最快的供應商，無需重寫整合，並可隨價格與品質變化切換。
- **模型排名與開發者文件:** 透過公開排名與排行榜比較模型、閱讀詳細文件，並以 CLI 或 MCP 伺服器接入代理工作流程。
- **工作室、工作流程與代理:** 建立多步驟流程、在互動式工作室測試提示詞，並用代理或工作流程功能串接多個模型產出最終成品。
- **用量計費的點數與單一帳單:** 以單一餘額按請求付費，依官方說法失敗任務不收費，不必為每個模型供應商管理最低消費。

**優勢:** 數百個影像、影片與音訊模型共用一把金鑰、一個餘額與一致請求格式; 不必為每個想嘗試的模型個別導入與管理供應商; 明確主打成本優勢，且依官方說法失敗任務不計費; 開發者介面完整：文件、CLI、MCP 伺服器、整合與狀態頁

**限制:** 将 API 整合進產品仍需開發能力; 各模型行為與參數不同，切換模型不見得是隨插即用; 成本隨用量上升，比固定訂閱更難編列預算; 功能頁面與模型供應狀況變動快速，文件可能落後

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

### MuAPI 與 Runware 的每月流量相比如何？

MuAPI 每月有 412,788 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？

MuAPI 的月增率為 +13.7%；Runware 為 +27.1%。

### 價格相比如何？

MuAPI：免費增值。採用量計費（pay-as-you-go）的點數制，並提供實驗用免費額度；官方標榜所有模型共用一個餘額、失敗任務不計費。各模型實際費率變動頻繁，請以定價頁面為準。 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 | [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) |
| 2 | [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) |
| 3 | [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) |
| 4 | [Kie.ai](https://openaitools.app/tw/tool/kie-ai-affordable-secure-deepseek-r1-api) | 2,275,553 | -22.4% | Pay-as-you-go | Multi-model AI API gateway for calling video, image, music, and chat models via one key. | [.md](https://openaitools.app/tw/tool/kie-ai-affordable-secure-deepseek-r1-api.md) |
| 5 | [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) |
| 6 | [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) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Flaq AI](https://openaitools.app/tw/tool/flaq-ai-api-platform) | 328,715 | +127.9% | 付費 | Unified API gateway providing developer access to diverse image, video, voice, and 3D models. | [.md](https://openaitools.app/tw/tool/flaq-ai-api-platform.md) |
| 10 | [Pollinations](https://openaitools.app/tw/tool/pollinations) | 316,875 | +22.8% | 免費 | Open-source infrastructure project providing a single API to generate images, video, speech, music, and text. | [.md](https://openaitools.app/tw/tool/pollinations.md) |

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來源：https://openaitools.app/tw/compare/muapi-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)