ComfyUI x Qwen-Image-Edit-2511：實現極高角色一致性的次世代圖像語意編輯實測（附工作流）

隨著生成式 AI 技術的演進，圖像編輯的精確度已成為使用者最在意的核心指標。在過去的 Stable Diffusion 生態系中，雖然我們可以透過 Inpainting（局部重繪）或是 IP-Adapter 來嘗試修改影像內容，但在面對「保持角色完全一致」且「大幅度更換服裝或姿態」的需求時，往往容易出現特徵偏移或細節崩壞的問題。阿里巴巴 Qwen 團隊在 2025 年 12 月下旬開源的 Qwen-Image-Edit-2511 則在語義理解與特徵保留上取得了突破性進展。這款模型不僅能夠精準理解複雜的編輯指令，還能在創意修改過程中極大程度地保留原始角色的身份特徵，讓「換裝」、「換背景」或「多人合成」等任務變得前所未有的簡單且穩定。

相較於先前版本的 Qwen-Image-Edit，2511 增強版在多個層面進行了顯著優化，特別是減少了圖像編輯過程中的「漂移」現象，這意味著在修改細節時，非修改區域的變動會更小。此外，該模型還強化了工業設計與材質替換的能力，並能生成輔助構造線。這對於設計師來說，不僅僅是一個繪圖工具，更是一個能夠理解空間幾何與設計邏輯的智能助手。為了驗證這款模型的實戰能力，本次我們在配備 RTX 5070 Ti（16GB VRAM）與 64GB 記憶體的硬體環境下進行測試，並分享一套優化過的工作流。

在硬體配置上，考慮到運算效率，我針對 ComfyUI 的官方工作流進行了關鍵優化：將原本的 bf16 模型替換為更適合一般硬體運行的 fp8mixed 版本，並結合了最新的 4-step Lightning 加速技術。這套優化方案讓一般消費級硬體設備更能輕鬆使用這個次世代圖像語意編輯工具，且完全不損及其在幾何推理與材質細節上的表現力。接下來，我們將透過實際的操作流程，帶大家一窺這款工具的強大潛力，並觀察其在二次元角色一致性上的優異表現。

📝 工作流（image_qwen_image_edit_2511.json）

將下列內容複製到文字編輯器，儲存為 image_qwen_image_edit_2511.json 後即可在 ComfyUI 匯入。

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▲ 啟動 ComfyUI 後，第一步是載入工作流環境。您可以點擊 LOGO 選單中的「File」並選擇「Open」，將我前文提供的工作流載入。

▲ 載入過程若系統提示「Missing Models」，代表模型目錄中缺乏必要的權重檔。這裡會列出四項核心組件包括：用於 Lightning 加速的 LoRA、處理影像與文字對應的文本編碼器、還原影像細節的 VAE 以及主幹擴散模型。確保這些檔案正確到位後，方能發揮 Qwen-Image-Edit-2511 的強大效能。可以點「Download」進行下載。

▲ 為了讓介面保持整潔並易於操作，複雜的節點邏輯封裝在子流程中。點擊該節點右上角的圖示，即可進入子流程檢視。

▲ 這是完整展開後的子流程。左側藍色區域負責管理所有核心模型的加載，中間綠色與紅色的語義編碼節點則是 Qwen-Image-Edit 的運算靈魂。它能同時解析多張參考圖並結合自然語言指令，將抽象的「換裝」或「局部編輯」概念精準轉化為模型可理解的特徵導引訊號。

▲ 在實際測試環節中，我們在「圖 1」上傳了萌芽娘角色的坐姿原圖，並在「圖 2」放入想更換的粉色連身裙。在 Prompt 框輸入指令「將圖2的服裝穿在圖1的角色身上」後點擊右上角的「Run」，系統便開始即時渲染。透過 Lightning LoRA 的優化，只需約半分鐘即可在最右側看到與角色特徵完美契合的編輯成品。

▲ 最終成品與原始圖片的對照圖，可以看出 Qwen-Image-Edit-2511 在角色特徵的「一致性」上表現極為出色。原本角色的髮色、瞳色及獨特的髮夾配件都被完整保留，服裝的自然光影與摺皺也與原圖畫風銜接得天衣無縫。這證明了該模型在處理高一致性要求任務時，具備了領先業界的穩定實力。