跳至主要內容
Kyeo AI
AI 影片模型
Google
Veo

Veo3.1 Quality

Veo3.1 Quality 是 Kyeo 目前採用 Veo 3.1 Quality 公開資料識別碼的 Veo 路線，純文字或 1～2 張首尾影格圖片的基礎請求固定 225 點數；成功後可另行發起 Extend、1080p 或 4K。Quality 是工作流程名稱，不代表每次結果都能達到固定的交付品質。

使用此模型查看點數費用回到模型廣場
能力標籤
文生影片、圖生影片
點數消耗
720p 225 · 1080p 233 · 4K 285
提示詞上限
5,000 字元
上傳限制
JPEG / PNG · 1–2 · 10 MB
30 秒快速瞭解
  • Kyeo 基礎生成固定 225 點數，成功後結果操作分別使用 225／8／60 點數
  • 無圖片自動走文字模式，1～2 張圖片自動走首尾影格模式
  • Google 官方與現行公開資料介面都列出參考圖片模式，但 Kyeo 對 Veo 3.1 Quality 明確拒絕
  • 目前 Veo 3.1 Quality 路徑接受文字或最多 2 張首尾影格圖片

熱門搜尋: Veo3.1 Quality 怎麼用 · Veo3.1 Quality 價格 · Veo3.1 Quality 和 Fast 差異

示例

Cinematic scene

Generate a video with the following specifications: Duration: 15 seconds Aspect Ratio: 16:9 Frame Rate: 24 fps 85mm prime lens with extremely subtle handheld breathing motion. Japanese airy film aesthetic blended with authentic Indonesian university life. Kodak Portra 400 cinematic color science, fine film grain, soft bloom, gentle gray haze, documentary-style realism. Primary color palette: Warm cream campus buildings, soft green trees, TransJakarta blue, MRT white and blue, cozy coffee shop browns, rainy gray skies, orange sunset, natural skin tones. Soft natural lighting transitions from fresh morning, rainy afternoon, golden sunset and peaceful city night. Foreground consists of softly blurred leaves, books, coffee cups, raindrops on glass, tote bags and passing students. Midground features a modern Indonesian university campus, library, campus café, rooftop, MRT station and TransJakarta stop. Background reveals Jakarta skyline, university buildings, trees, city traffic and warm evening lights. Everything feels calm, productive, cozy and unmistakably Indonesian. Main Character Exceptionally beautiful Indonesian university student. 20 years old. Long slightly wavy black hair. Natural makeup. Warm tan skin. Oversized beige cardigan. White inner shirt. Light blue wide-leg jeans. White sneakers. Cream canvas tote bag. Silver laptop. -------------------------------------------------- SHOT 1 (0–2s) Early morning. The young woman waits at a TransJakarta bus stop. A TransJakarta bus arrives. She taps her card and boards the bus with a gentle smile. Morning sunlight shines through the windows. The camera follows naturally beside her. -------------------------------------------------- SHOT 2 (2–4s) Inside a quiet university library. She opens her laptop beside several textbooks. She writes notes while reading. Other students quietly study in the background. Soft morning light enters through large windows. The atmosphere feels peaceful and productive. -------------------------------------------------- SHOT 3 (4–6s) Campus coffee shop. A hot latte sits beside her laptop. She types her assignment while occasionally sipping coffee. Steam rises naturally from the cup. She smiles slightly after finishing a paragraph. The handheld camera gently circles around her. -------------------------------------------------- SHOT 4 (6–8s) Rain begins outside the campus. She walks beneath a transparent umbrella. Raindrops hit the pavement. Students run toward nearby buildings. She enjoys the rain while quietly smiling. The camera slowly tracks beside her. -------------------------------------------------- SHOT 5 (8–10s) Lunch break. She sits at a small bakso stall near campus. A steaming bowl of bakso is placed in front of her. She gently blows on the spoon before taking the first bite. Her face immediately lights up with a satisfied smile. The stall owner continues serving customers in the background. -------------------------------------------------- SHOT 6 (10–12s) Late afternoon. She stands on the rooftop of the university building. The Jakarta skyline glows beneath a beautiful orange sunset. A gentle breeze moves her hair. She quietly enjoys the peaceful moment while holding a cup of coffee. -------------------------------------------------- SHOT 7 (12–14s) Several close friends join her. They laugh naturally. One friend raises a smartphone. Everyone gathers together for a selfie. The camera captures genuine laughter and candid expressions. -------------------------------------------------- SHOT 8 (14–15s) Night. She rides the MRT home. Sitting beside the window, wearing wireless earbuds. Jakarta city lights pass outside. She looks out the window with a peaceful smile. The train continues moving through the city. Natural fade to black. -------------------------------------------------- Audio Morning city ambience. TransJakarta doors. Library ambience. Keyboard typing. Coffee shop sounds. Rain. Bakso stall ambience. Light wind. Friends laughing. MRT announcements. Train movement. No narration. No dialogue. No background music. -------------------------------------------------- Negative Prompt No body deformation. No facial distortion. No plastic skin. No excessive beauty filter. No CGI appearance. No hard cuts. No white flash transitions. No watermark. No logo. No subtitles. Ultra-realistic. Looks exactly like a premium cinematic university vlog filmed in Jakarta, Indonesia during 2026. Authentic Gen Z lifestyle, natural facial expressions, documentary-style handheld cinematography, emotionally immersive student life, and realistic everyday moments.

Cinematic scene

Main subject: Young Japanese woman, early 20s, natural everyday appearance, cream oversized knit cardigan over a white ribbed tank top, light blue relaxed-fit denim jeans, worn brown leather loafers, simple silver stud earrings, black shoulder-length straight hair worn loose with soft bangs. Realistic skin texture, minimal makeup, calm and thoughtful personality. Maintain consistent identity, clothing, hairstyle, and appearance throughout the entire video. Location: Authentic Japanese seaside fishing town during a quiet golden-hour evening. Narrow streets leading toward the harbor, weathered wooden homes, fishing nets drying outside, small flower pots near entrances, bicycles parked beside fences, concrete seawalls, utility poles, overhead cables, distant fishing boats, gentle ocean breeze, warm sunset light reflecting from windows. No tourist attractions, restaurants, advertisements, crowds, or commercial activity. Visual Style: Ultra-realistic observational documentary. Quiet slice-of-life storytelling with genuine human behavior. Natural pacing. Rich environmental details. Authentic everyday imperfections. Emotion conveyed through subtle expressions instead of performance. Camera Style: Late-1990s MiniDV home camcorder aesthetic. Friend or family member casually documenting ordinary life. Constant handheld movement with uneven framing, occasional accidental zoom adjustments, autofocus breathing, slight tape compression artifacts, mild interlacing, soft highlight blooming, washed-out colors, subtle chroma noise, imperfect white balance, rolling shutter, occasional dropped frames, no stabilization, no cinematic movements, no modern color grading. 00:00–00:02 Outside a weathered wooden house facing a quiet side street. She slides open the front door carrying a small watering can and gently waters potted flowers near the entrance. The camera begins recording a little too early and briefly points toward the ground before finding her. 00:02–00:04 She walks slowly toward the narrow lane leading to the harbor. A bicycle passes quietly in the background. The camera operator falls slightly behind, causing loose framing and gentle handheld sway. 00:04–00:06 She pauses beside a low seawall, watching gentle waves while seagulls fly overhead. Wind softly lifts her hair. Autofocus repeatedly shifts between her profile and the distant boats. 00:06–00:08 She bends down to pick up a smooth seashell near the shoreline and quietly examines it before smiling to herself. Warm sunlight reflects across the water as exposure subtly fluctuates. 00:08–00:10 She sits on a wooden bench overlooking the harbor, holding a warm canned tea from a convenience store purchased earlier. She quietly watches fishing boats returning while absentmindedly brushing hair behind her ear. The camera slowly drifts as if the person filming becomes distracted by the scenery. 00:10–00:12 Close side profile. Someone off-camera asks if she's ready to head home. She turns naturally, smiles with quiet warmth, nods, and softly replies, "Un." The camcorder reacts slightly late, briefly losing focus before recovering. 00:12–00:15 She walks along the seawall toward the sunset, occasionally glancing back at the camera with a genuine smile before looking ahead again. The recording abruptly stops mid-step with a brief tape glitch and cuts instantly to black. Audio: Natural ambient sound only — gentle ocean waves, distant seagulls, light wind, rustling leaves, quiet footsteps on pavement, faint boat engines far away, soft neighborhood ambience, bicycle wheels passing occasionally, fabric moving in the sea breeze. No music. No narration. No sound design. Goal: An intimate, forgotten MiniDV family recording from coastal Japan in the early 2000s—quiet, nostalgic, imperfect, deeply authentic, and emotionally understated.

Cinematic scene

Main Subject: Young Korean woman, early 20s, soft pastel cardigan over a light dress, hair in loose waves with a small flower clip, warm gentle expression. Location: Public park lined with blooming cherry blossom trees, mid-afternoon. A picnic mat spread on the grass, a small basket, petals drifting in the breeze. No crowds, no commercial elements. Visual Style: Ultra-realistic documentary realism, soft romantic candid feeling, warm dappled spring light. Camera Style: Early 2000s DV camcorder, handheld gentle drift, autofocus adjusting between her and drifting petals, soft faded pastel tones, mild grain. No stabilization. Timeline (15 sec, each slot = 2 compressed beats): 00:00–00:03 → She sits on the picnic mat, then reaches up to catch a falling petal. 00:03–00:06 → She examines it in her palm, then says to camera "이거 진짜 예쁘다" ("This is really pretty"). 00:06–00:09 → She opens the small basket, pulling out a sandwich to eat. 00:09–00:12 → A breeze scatters more petals around her; she laughs, brushing them from her hair. 00:12–00:15 → She looks at camera saying "봄이 진짜 좋다" ("I really love spring"), smiling as it fades. Audio: Wind rustling blossoms, distant birds, faint footsteps nearby, fabric rustling. Her dialogue as noted above. No music. Goal: A soft, romantic spring picnic moment gentle, warm, deeply authentic.

Cinematic scene

Main subject: young Japanese woman, early 20s, natural everyday appearance, faded sage-green sleeveless crop top, loose relaxed-fit cropped trousers, white canvas sneakers, thin gold chain necklace, black straight hair in a low messy bun with face-framing strands. Realistic skin texture, minimal makeup, soft and gentle personality. Maintain consistent identity, clothing, hairstyle, and appearance throughout the entire video. Location: Authentic Japanese residential neighborhood during a calm late morning. Narrow paved streets, low-rise wooden and stucco homes, small entryways with potted plants, bicycles leaning against walls, vending machine absent, utility poles, tangled overhead wires, mature trees casting moving shadows, quiet suburban atmosphere. No stores, advertisements, cafés, crowds, or commercial activity. Visual Style: Ultra-realistic documentary realism. Genuine candid behavior. Natural body language. Unscripted slice-of-life feeling. Strong environmental authenticity. Rich real-world details and believable human motion. Camera Style: Early-2000s consumer DV camcorder aesthetic. Friend casually recording everyday moments. Heavy handheld shake, imperfect framing, frequent autofocus hunting, lens breathing, exposure pumping when moving between sun and shade, occasional motion blur, subtle rolling shutter, mild digital compression artifacts, faded colors, soft contrast, slight sensor noise. No stabilization. No cinematic camera moves. No modern color grading. **00:00–00:02** Outside a small house entrance. She sits on a low wooden step tying her sneaker laces. A light breeze moves loose strands of hair. She smiles naturally while the camera struggles to hold focus. **00:02–00:04** The camera follows her into a narrow street lined with potted plants and low walls. She notices a stray cat approaching and crouches down. Framing drifts off-center as the operator tries to keep up. **00:04–00:06** She gently pets and feeds the cat. Autofocus repeatedly shifts between her face and the animal. Morning sunlight flickers through leaves overhead. **00:06–00:08** Small front yard beside her house. She hangs laundry on a balcony rack while fabrics sway in the breeze. Exposure changes as clouds briefly pass overhead. **00:08–00:10** On a quiet engawa (wooden porch) with a ceramic tea cup. She sits comfortably watching the neighborhood, occasionally brushing hair behind her ear. Loose handheld side angle with natural camera drift. **00:10–00:12** Close side profile. Someone off-camera greets her. She turns, raises her hand, smiles warmly, and casually says, "Ohayou." The camera catches the moment slightly late. **00:12–00:15** Walking slowly down a tree-lined residential lane holding her tea cup. She notices the camera, gives a small genuine smile, then looks away and continues walking. Recording cuts abruptly to black mid-motion as if the camcorder was switched off. Audio: Natural ambient sound only — morning birds, distant scooters, light wind, leaves rustling, faint neighborhood chatter, cat sounds, footsteps on pavement, fabric moving on a balcony rack, subtle residential ambience. No music. No sound design. No narration. Goal: Authentic Japanese neighborhood life captured like a forgotten home video from the early 2000s — candid, imperfect, realistic, warm, and deeply believable.

Cinematic scene

Create an ultra-realistic 90-second cinematic romantic comedy featuring the same young East Asian woman throughout the entire sequence. Maintain identical facial features, soft shoulder-length black hair with bangs, glowing skin, body proportions, and natural expressions in every scene. She wears a fitted white sleeveless crop top, light blue denim shorts, white sneakers, a pearl choker, delicate bracelets, rings, and carries a small white shoulder bag. Premium Korean drama aesthetic, warm natural lighting, realistic performances, cinematic handheld and gimbal camera work, shallow depth of field, soft color grading, and photorealistic 4K HDR. The film opens with the girl waking up in her cozy bedroom after hearing a notification. She excitedly reads a message on her phone from someone she recently matched with that says, "See you at 5 PM." She smiles, stretches happily, and begins getting ready. She styles her hair, applies light makeup, chooses her favorite outfit, sprays perfume, checks herself in the mirror, grabs her handbag, and leaves home feeling excited. She walks through sunny city streets toward a stylish café. Warm afternoon light fills the streets as she happily imagines meeting him for the first time. She orders an iced coffee and waits by the window. Every time the café door opens, she looks up with excitement, but each time it is someone else. Minutes pass and her smile slowly fades. Finally, she leaves the café feeling embarrassed and disappointed. As she steps outside, she accidentally bumps into a handsome young man carrying two iced coffees. One cup spills slightly onto both of them. They immediately apologize before bursting into laughter. He offers her the second untouched coffee and jokingly says, "Looks like this one was meant for you." They begin walking together through a peaceful park, talking naturally as if they've known each other for years. They laugh about funny childhood stories, feed pigeons, browse a small bookstore, share street snacks, and take playful selfies together. Their chemistry grows effortlessly while the afternoon turns into golden hour. During their walk, she casually checks her phone again and suddenly freezes. She realizes the original message actually said "Tomorrow at 5 PM." She laughs uncontrollably and shows him the screen. He laughs too before smiling warmly and saying, "Good... because otherwise we never would've met." As evening arrives, they continue walking side by side along a beautiful riverside promenade. City lights begin reflecting on the water while the sunset paints the sky orange and pink. They stop at the railing, quietly watching the skyline. He gently reaches for her hand. She smiles, accepts without hesitation, and they continue walking together toward the glowing city lights. The final cinematic shot slowly pulls back as they disappear into the sunset hand in hand, laughing together, suggesting that the best moments sometimes begin with the wrong plan. Natural ambient audio only: bedroom ambience, birds chirping, footsteps, café chatter, coffee pouring, distant traffic, park ambience, laughter, bookstore pages turning, river breeze, soft city sounds, and evening ambience. No background music, no subtitles, no logos, no watermarks, and no on-screen text. Premium Korean drama cinematography, realistic emotions, elegant camera movements, shallow depth of field, warm cinematic color grading, 16:9 widescreen, 4K HDR.

Cinematic scene

A 15-second photorealistic Korean beauty commercial for a premium cushion foundation. Use @image1 as the exact reference for the model, product, and visual style. A young Korean woman sits in a bright minimalist room with soft daylight. She looks at her reflection in the mirror, notices uneven skin, then opens a pearl-beige cushion compact. Show elegant macro shots of the cushion, puff, and smooth foundation texture. She gently taps the cushion onto her cheek and face. The skin becomes naturally fresh, luminous, and smooth while keeping realistic pores and texture. Show close-up beauty shots with soft Korean TV commercial cinematography. She walks outside under warm sunlight, looking confident and radiant. End with a premium product hero shot of the cushion compact with soft background blur. Audio: soft Korean beauty commercial music, subtle product sounds, gentle female Korean voice.

一句話瞭解

這個模型表現如何？

輸入路徑、隱藏片長／解析度、聲音差異、參考圖片裁剪與四種扣點必須分別核對。

它擅長什麼
目前定位是 Kyeo 的公開資料 Veo 3.1 Quality 基礎與結果操作頁，不是 Google `veo-3.1-generate-001` 的完整鏡像，也沒有實測證明固定品質等級。
適合哪些使用者
適合用非關鍵文字或首尾影格素材驗證目前高扣點路線與結果操作，不適合在實際輸出和帳務閉環前作為交付承諾。
為什麼要在 Kyeo AI 使用
Kyeo 顯示比例、浮水印、隨機種子與翻譯，基礎 225 點數並開放三項結果操作；但參考圖片、片長、解析度、聲音與 C2PA 合約都未完整呈現。

關鍵參數總覽

協助你快速評估此模型是否符合你的業務情境。

模型類別
AI 影片模型
廠商
Google
模型家族
Veo
整合方式
目前站內整合
執行方式
非同步任務
提示詞上限
5,000 字元
上傳限制
JPEG / PNG · 1–2 · 10 MB

其他名稱

同一個模型在官方文件、社群討論與 API 串接層可能有不同稱呼，這裡幫你統一整理。

Veo3.1 Quality
Google Veo
Veo Video

使用者常見問題

從實際任務、輸入條件和結果要求出發，整理選擇模型時最需要確認的問題。

Veo3.1 Quality 怎麼用
Veo3.1 Quality 價格
Veo3.1 Quality 和 Fast 差異
Veo3.1 Quality 和 Lite 差異
Veo3.1 Quality 支援參考圖模式嗎
Veo3.1 Quality Extend 是什麼
Veo3.1 Quality Get 1080P 是什麼
Veo3.1 Quality Get 4K 是什麼
Veo3.1 Quality 適合正式交付嗎
Kyeo AI 的 Veo3.1 Quality 與 Google 官方 Veo 3.1 有什麼區別？

選擇指南

還在猶豫該用哪個模型嗎？先查看這幾個關鍵決策點。

1
什麼情況可以先測試

當你需要驗證 Kyeo 目前 Veo 3.1 Quality 路線，並能接受 225 點數的單次基礎扣點，可以用非關鍵素材進行受控測試；在實際輸出與退款閉環前，不應直接用於交付。

2
什麼時候先比較其他模型

若需要 Kyeo AI 的參考圖片路徑，只能比較 Fast；這是目前站內頁面的功能範圍，不代表官方模型的固定差異。

3
最小驗證路徑

先用一條非敏感文字或首尾影格請求核對狀態、比例、像素、片長、音軌、C2PA、網址期限與 225 點數；基礎結果合格後，再分別驗證 Extend、1080p 與 4K。

使用者常搜尋的比較

把常見候選放在同一任務下比較，協助你確認輸入方式、控制項和成本差異。

Veo3.1 Quality 和 Veo3.1 Fast 差異
Veo3.1 Quality vs Veo3.1 Fast
Veo3.1 Quality 和 Veo3.1 Lite 差異
Veo3.1 Quality vs Veo3.1 Lite
Veo3.1 Quality 和 Sora 2 Pro 差異
Veo3.1 Quality vs Sora 2 Pro

模型比較表

還在猶豫該選哪一個嗎？這張表協助你快速看清目前模型與替代方案的核心差異。

在 Kyeo AI 中的目前定位
Veo3.1 Quality
Veo 高品質交付檔
Veo3.1 Fast
Veo 主入口 / 路徑完整快速檔
Veo3.1 Lite
基礎生成輕量檔
生成模式
Veo3.1 Quality
基礎文生 / 圖生
Veo3.1 Fast
文字 + 首尾幀 + 參考圖
Veo3.1 Lite
基礎文生 / 圖生
結果動作
Veo3.1 Quality
支援 Extend / 1080P / 4K
Veo3.1 Fast
同樣支援結果操作
Veo3.1 Lite
目前不支援這些動作
基礎價格口徑
Veo3.1 Quality
固定 225 點數
Veo3.1 Fast
固定 30 點數
Veo3.1 Lite
固定 15 點數
更適合的階段
Veo3.1 Quality
方向已定後的高預算交付對照
Veo3.1 Fast
做完整 Veo 路線驗證
Kling 3.0
更適合的階段 — Kling 3.0: 目前可用的同類模型，可從詳情頁繼續比較功能與價格。

實際使用體驗

結合公開資料、目前站內邊界和典型任務，說明模型適合與不適合的情況。

Veo：快速試用亮點

差異必須透過同題結果驗證。

官方、公開資料介面與 Kyeo 的參考圖片邊界不同

Google 官方、公開資料介面與 Kyeo 對參考圖片模式的支援範圍並不相同，不能用其中一方的說明替另一方背書。

功能詳解

兩種站內基礎輸入路徑

Kyeo 無圖片時送出 `TEXT_2_VIDEO`，有 1～2 張圖片時自動送出 `FIRST_AND_LAST_FRAMES_2_VIDEO`；超過 2 張首尾影格圖片會拒絕，Veo 3.1 Quality 參考模式也會拒絕。

結果操作依賴站內成功任務

Extend、1080p 與 4K 只對歸屬、模型和狀態符合條件的 Kyeo 成功任務開放，並沿用原始外部任務 ID。

Veo：透明點數規則

Kyeo AI 只顯示 `aspectRatio / seeds / enableTranslation / watermark`，沒有 4／6／8 秒、720p／1080p／4K、聲音或 C2PA 控制項；實際預設值與輸出必須從任務結果核對。

適合做什麼

Veo：日常創作

使用非關鍵提示詞確認請求、回呼、實際片長、像素、音軌、C2PA、網址期限與 225 點數，不把一次成功當作品質保證。

Veo：內容迭代

用 1 張起始圖片或 2 張首尾圖片核對格式、大小、比例、順序與輸出；目前上限 2 張，不等於支援素材參考。

Veo：方案比較

基礎結果合格後，分別驗證 Extend、1080p、4K 的狀態、處理時間、實際像素、片長、音軌、網址期限與額外扣除點數。

提示詞技巧

先確認輸入路徑與 225 點數風險

Quality 不是預設的試錯頁。更合理的做法是先用 Lite／Fast 或其他模型跑通方向，再用 Quality 做正式對照。

不要把首尾影格當作素材參考圖

Kyeo 目前 Veo 3.1 Quality 只接受起始／結束影格，不接受素材參考模式。若任務依賴角色或風格素材，頁面應明確說明這是目前頁面範圍，而不是暗示兩張圖片會承擔參考職責。

逐項驗證結果操作

每項都要分別檢查實際像素、編碼、音軌、內容連續性、網址期限與扣點。

選擇它的理由

純文字與首尾影格路徑會依圖片數量自動選擇。
首尾幀模式最多支援 2 張圖片。
成功任務可進入 Extend、1080p 與 4K 操作。
基礎與三項結果操作使用分開的站內扣點。

使用前須知

Quality 層級仍需用目標素材檢查畫面、動作、文字和交付適用性。
目前 Kyeo Quality 工作流程不提供獨立的參考圖片模式。
片長、解析度、聲音與 C2PA 沒有在基礎表單和結果合約中完整呈現。
使用 Veo 時，建議先依所選參數生成一個代表性樣本，確認效果符合目標後再擴大批次。

可調整參數

協助你快速評估此模型是否符合你的業務情境。

生成模式
可選
參數類型: select
依已提交圖片決定
TEXT_2_VIDEO
FIRST_AND_LAST_FRAMES_2_VIDEO
寬高比
可選
參數類型: select
預設值: 16:9
橫向 (16:9)
直向 (9:16)
自動裁切 (Auto)
解析度
可選
參數類型: select
720p
720p — 225
1080p — 233
4K — 285
時長
可選
參數類型: select
8 s
4 s
6 s
8 s
浮水印文字
可選
參數類型: text
提示詞翻譯
可選
參數類型: select
預設值: true
自動翻譯為英文
保留原文

點數消耗

依解析度為 225 / 233 / 285 點數

直接生成 720p 扣 225 點數，1080p 扣 233 點數（232.5 無條件進位），4K 扣 285 點數。Extend 扣 225；符合條件的 1080p、4K 結果操作另扣 8、60 點數。

省點數小技巧

批次生成圖片或影片前，建議先用同一組素材，在目前模型與同類候選模型之間進行 A/B 測試；確認效果後再批次生成，避免浪費點數。

常見問題

同類模型推薦

還沒決定該用哪個嗎？順便比較一下這幾個同類候選模型。

Veo3.1 Fast

Kyeo AI 的 Veo3.1 Fast 支援純文字、首尾影格與參考圖片生成，可直接選擇 720p、1080p、4K，以及 4、6、8 秒時長。 依解析度為 30 / 38 / 90 點數.

AI 影片模型
依解析度為 30 / 38 / 90 點數
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Veo3.1 Lite

Kyeo AI 的 Veo3.1 Lite 支援純文字、首尾影格與參考圖片生成，可直接選擇 720p、1080p、4K，以及 4、6、8 秒時長。 依解析度為 15 / 23 / 75 點數.

AI 影片模型
依解析度為 15 / 23 / 75 點數
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Kling 3.0

瞭解 Kyeo AI 的 Kling 3.0 影片：3～15 秒、單鏡頭與最多 5 個多鏡頭、首尾幀、聲音，以及 std／pro／4k 每秒費率。 適合指定起始／結束幀，或把一段 3～15 秒概念拆成最多 5 個短鏡頭。人物一致性、對嘴、文字、聲音與鏡頭銜接仍須依實際結果驗收。

AI 影片模型
每次 42～1005 點數
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資訊來源

頁面內容依據廠商資料、模型系列說明與 Kyeo AI 平台串接設定整理。

來源說明

本頁描述目前已驗證的站內合約，不公開也不依賴內部供應商模型識別碼。

最後更新: 2026-08-28
Google Cloud: Veo 3.1 models
官方
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Google Cloud: Veo on Vertex AI video generation API
官方
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Google Cloud: Veo preview 工作流程 deprecation
官方

Google 已要求從 Veo 3.1 preview ID 遷移到穩定版 `-001` ID。

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