# ComfyOnline vs Replicate AI

ComfyOnline 每月有 19,465 次造訪，月增率 -30.7%，定價模式為免費增值、付費。Replicate AI 每月有 904,038 次造訪，成長率 -8.4%，定價模式為付費。

| 指標 | [ComfyOnline](https://openaitools.app/tw/tool/comfyonline) | [Replicate AI](https://openaitools.app/tw/tool/replicate-ai) |
| :--- | :--- | :--- |
| 網站網址 | https://www.comfyonline.app | https://replicate.com |
| 分類 | AI API, AI 開發者工具, AI 圖像生成器, AI Video Generator | AI API, AI 模型, AI 開發者工具, 開源 AI 模型 |
| 定價模式 | 免費增值、付費 | 付費 |
| 每月造訪次數 | 19,465 | 904,038 |
| 月成長率 | -30.7% | -8.4% |
| 主要市場 | 美國 | 美國 |
| 直接造訪 | 7,798 | 577,501 |
| 評論分數 | 4.3 | 4.6 |
| 收藏數 | 1 | 5 |
| 支援平台 | 網站 | 網站 |

## ComfyOnline

ComfyOnline 把 ComfyUI 這個熱門的節點式擴散模型介面搬進瀏覽器。你能用與本地相同的節點生態建立或匯入節點圖，運算則跑在 RTX 4090、A6000、L40S、A100、H100 等雲端 GPU 上。編輯工作流免費，僅在工作流實際執行時按秒計費，正是官方強調的 serverless 模式。

差異化重點在部署。工作流不會停留在一次性實驗，ComfyOnline 能自動為其產生 API 端點，讓工作流成為可被自有產品呼叫的服務。平台也在同一畫布接入第三方模型：影片端有 Kling、Runway、Luma、Pika、Wan；圖像端有 Flux Pro Ultra、Ideogram、Recraft；語音端有 ElevenLabs；文字端可呼叫 Claude、Gemini、GPT、DeepSeek。這讓它成為混合開源擴散管線與商業模型 API 的統一控制台。

價格採額度制而非固定方案。儲值從約 10 美元起，個人、新創、企業等月費會員提供更大額度包、relax 模式佇列與私有 LoRA 及模型等客製能力。由於生成成本取決於 GPU 等級與執行時間，團隊應以按秒額度費率作為主要預算依據。

**價格與方案:** 免費加付費：編輯工作流免費，僅為執行時間付費。隨量儲值額度包約 10 美元起（含贈送額度），個人、新創、企業等月費會員提供更大額度包、無限 relax 模式佇列與客製部署選項。

- **雲端 ComfyUI 工作區:** 在瀏覽器中於 4090、A6000、L40S、A100 或 H100 上建立與執行節點圖，常用自訂節點已預裝。
- **一鍵 API 部署:** 將任意工作流自動生成 API 端點，無需自行撰寫服務層即可被自有應用呼叫。
- **內建模型代理:** 在同一畫布使用 Kling、Runway、Luma、Pika、Wan 生成影片，Flux Pro Ultra、Ideogram、Recraft 生成圖像，ElevenLabs 合成語音，以及 Claude、Gemini、GPT、DeepSeek 處理文字。
- **按秒計費:** 編輯不收費，僅按工作流執行秒數計費，閒置 GPU 不產生費用。
- **私有模型與彈性擴充:** 可上傳私有權重與 LoRA，部署可隨流量自動擴充。

**優勢:** 無需本地 GPU，執行於高效能雲端顯卡; 工作流轉 API 省下大量後端工作; 第三方影片、圖像、音訊、LLM 整合覆蓋廣泛; 按秒計費透明，閒置不收費

**限制:** 按秒額度不易預估實際花費; 部分高階 GPU 等級需升級特定方案; 文件與企業條款不如大型雲端廠商完整

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

## Replicate AI

Replicate is a cloud API for running, fine-tuning, and deploying machine learning models. Spin up open-source and hosted models — from image, video, and audio generation to speech synthesis, captioning, and LLM inference — with one line of code, or package your own model with Cog and put it behind a production-ready API.

**價格與方案:** Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

- **Thousands of models behind one API:** Run image, video, audio, speech, and language models through a uniform API surface, with official models for FLUX, Nano Banana, Seedream, Grok Imagine, MiniMax, Wan, Seedance, and more.
- **One-line-of-code inference:** Set up a model in minutes and make an API call in Python, Node, or plain HTTP after authenticating with an API token.
- **Cog packaging and custom deployments:** Package your own model with Cog, an open-source tool for packaging machine learning models, and deploy it on dedicated hardware that scales up and down with demand.
- **Model fine-tuning:** Fine-tune models on your own data, including fast-booting fine-tunes that are billed only while actively processing requests rather than for idle time.
- **Published hardware and inference rates:** Transparent per-second hardware rates across CPU, T4, L40S, A100, H100, and H200 configurations, with committed-spend options for multi-GPU capacity.

**優勢:** Very broad model catalog spanning image, video, audio, speech, and LLMs behind one consistent API; Usage-based billing with openly published per-second hardware and per-output model rates; Cog makes it straightforward to package and deploy your own private models; Automatic scaling handles traffic spikes without manual capacity planning

**限制:** Costs are consumption-based and can rise quickly with heavy traffic or always-on private deployments; Private models bill for idle and setup time, not just request processing, unless they are fast-booting fine-tunes; Long-running GPU models can queue on shared public capacity during peak periods; It is an infrastructure layer, so you still need your own prompts, pipelines, and application code

[Profile (Markdown)](https://openaitools.app/tw/tool/replicate-ai.md)

## 常見問題

### ComfyOnline 與 Replicate AI 的每月流量相比如何？

ComfyOnline 每月有 19,465 次造訪，而 Replicate AI 有 904,038。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？

ComfyOnline 的月增率為 -30.7%；Replicate AI 為 -8.4%。

### 價格相比如何？

ComfyOnline：免費增值、付費。免費加付費：編輯工作流免費，僅為執行時間付費。隨量儲值額度包約 10 美元起（含贈送額度），個人、新創、企業等月費會員提供更大額度包、無限 relax 模式佇列與客製部署選項。 Replicate AI：付費。Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

## 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 | 擅長跨各種供應商路由文字與多模態提示詞，但缺乏 Replicate 的專屬自訂 ML 部署。 | [.md](https://openaitools.app/tw/tool/openrouter-ai.md) |
| 2 | [fal.ai](https://openaitools.app/tw/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | 影像與視訊模型的無伺服器執行速度更快，但自訂模型部署的通用性不如 Replicate。 | [.md](https://openaitools.app/tw/tool/fal-ai.md) |
| 3 | [BytePlus](https://openaitools.app/tw/tool/byteplus) | 3,036,127 | -30% | 免費增值、付費 | 為企業打造的 AI 原生雲平台 | [.md](https://openaitools.app/tw/tool/byteplus.md) |
| 4 | [RunPod](https://openaitools.app/tw/tool/runpod) | 2,881,043 | +5.9% | 付費 | 面向 AI 開發者的 GPU Pod、Serverless 推論與叢集雲平台 | [.md](https://openaitools.app/tw/tool/runpod.md) |
| 5 | [Together AI](https://openaitools.app/tw/tool/together-ai) | 1,645,930 | +64.9% | 免費增值、付費 | 更著重於 LLM 推論與微調，但缺乏 Replicate 那種由社群策展的多樣化媒體模型目錄。 | [.md](https://openaitools.app/tw/tool/together-ai.md) |
| 6 | [Vast.ai](https://openaitools.app/tw/tool/vast-ai) | 1,257,554 | +2.8% | 付費 | 從全球市集以秒為單位租用雲端 GPU | [.md](https://openaitools.app/tw/tool/vast-ai.md) |
| 7 | [Modal](https://openaitools.app/tw/tool/modal-com) | 1,196,021 | +30.2% | 免費增值、需聯絡報價 | 為 AI 與資料工作負載打造的无伺服器雲端基礎設施 | [.md](https://openaitools.app/tw/tool/modal-com.md) |
| 8 | [Unsloth AI](https://openaitools.app/tw/tool/unsloth-ai) | 887,457 | -17.6% | 免費 | Specializes specifically in ultra-efficient model fine-tuning, rather than providing a general-purpose model hosting API. | [.md](https://openaitools.app/tw/tool/unsloth-ai.md) |
| 9 | [Atlas Cloud](https://openaitools.app/tw/tool/atlas-cloud) | 777,031 | -16.4% | 付費 | Offers a broad mix of generative media models via API, but lacks Replicate's massive community deployment ecosystem. | [.md](https://openaitools.app/tw/tool/atlas-cloud.md) |
| 10 | [Salad](https://openaitools.app/tw/tool/salad-gpu-cloud) | 713,519 | +10.4% | 免費試用、付費、需聯絡報價 | 編排全球閒置消費級 GPU 的分散式 GPU 雲 | [.md](https://openaitools.app/tw/tool/salad-gpu-cloud.md) |

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來源：https://openaitools.app/tw/compare/comfyonline-vs-replicate-ai

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)