ChatGPT Images 2.5評測：出圖快五成，雜訊被網友抓包 | ChatGPT Images 2.5 Review: 50% Faster, Noise Complaints

By Kit 小克 | AI Tool Observer | 2026-09-11

🇹🇼 ChatGPT Images 2.5評測：出圖快五成，雜訊被網友抓包

ChatGPT Images 2.5 是 OpenAI 於 2026 年 9 月 8 日推出的新一代圖像模型，官方主打「延遲砍半、細節更精準」。但同一週 Reddit 上就冒出一片「雜訊很醜」的抱怨，跟官方文案完全對不上。這篇整理實際測出來的優缺點，讓你決定要不要跳槽用它做圖。

新增功能：Sketch 手繪參考、多輪編輯更穩

這次最大的介面改動是 Sketch：在對話框輸入「@Sketch」就能直接手繪草圖當參考，搭配海報、周邊商品等現成範本使用。另外新增「圖片留言」功能，可以針對畫面局部下指令做局部修改，不用整張重畫；生成的圖片也能附上原始提示詞讓別人直接沿用。官方強調 ChatGPT Images 2.5 在多輪對話中保留主體一致性的能力變好，處理透明背景、複雜版面也更穩。

速度快五成，但雜訊被 Reddit 抓包

OpenAI 宣稱生成延遲比上一代 Images 2.0 降低最多 50%，光線與材質也更自然。實際用起來速度確實有感，但品質這塊爭議很大：不少 Reddit 用戶回報畫面出現明顯顆粒雜訊，甚至有人直接說「這些雜訊讓它幾乎沒辦法用在正式產出上」。TechRadar 記者自己重測後也認同這個抱怨是真的，不是個案。換句話說，ChatGPT Images 2.5 犧牲了一點畫面乾淨度去換速度，官方文案沒提到這個 trade-off。

API 定價：Flare 與 Sunburst 怎麼選

API 端推出兩個型號，價格完全一樣：每百萬圖像輸入 token 8 美元（快取 2 美元）、輸出 30 美元、文字輸入 5 美元（快取 1.25 美元）。GPT-Image-2.5 Flare 是預設款，主打速度與量產，適合社群內容、電商圖、快速原型；GPT-Image-2.5 Sunburst 走精緻路線，編輯控制更細，生成時間較長，適合正式的行銷素材。消費端 ChatGPT App 內使用不額外收費，算在既有訂閱方案裡，但仍受速率限制。

安全性：深偽風險官方自己也承認

System Card 裡寫得很白：畫面越逼真，深偽濫用風險就越高。實測不安全生成比例 Sunburst 為 1.09%、Flare 為 1.41%，都比舊版 Images 2.0 的 1.64% 略低，但不是零。輸出圖片內建 C2PA 中繼資料與隱形浮水印，方便日後追溯來源。

該不該換？

需要快速出量、對雜訊容忍度高（社群貼文、草稿用途），Flare 值得換過去，速度提升是真的
正式商用素材、印刷品這類對畫面乾淨度要求高的場景，先拿目前正在跑的圖對比測試，別急著全面切換
用 Sketch 手繪參考的工作流程如果吃這一套，這是目前市面上少數整合得這麼直覺的功能

好不好用，試了才知道。

🇺🇸 ChatGPT Images 2.5 Review: 50% Faster, Noise Complaints

ChatGPT Images 2.5, OpenAI's newest image model launched September 8, 2026, promises up to 50% lower latency and sharper editing precision. But the same week it shipped, Reddit lit up with complaints about ugly noise patterns, a story that doesn't quite match the marketing copy. Here's what actually holds up.

What's New: Sketch References and Steadier Multi-Turn Edits

The headline feature is Sketch: type "@Sketch" in the chat to draw directly and use it as a visual reference, paired with ready-made templates for posters, merch, and other common formats. A new image-comments feature lets you target specific regions for revision instead of regenerating the whole image, and generated images can carry their source prompt for others to reuse. OpenAI says ChatGPT Images 2.5 now holds subject consistency better across multi-turn conversations and handles transparent backgrounds and complex layouts more reliably.

50% Faster, But Reddit Caught the Noise

OpenAI claims generation latency dropped up to 50% versus Images 2.0, plus more natural lighting and textures. The speed gain is real and noticeable in practice, but image quality is where things get contentious: multiple Reddit users reported visible grainy noise, with one calling it "mostly useless for production." A TechRadar reporter re-tested independently and agreed the complaints held up, this wasn't an isolated case. In short, ChatGPT Images 2.5 traded some cleanliness for speed, a trade-off OpenAI's announcement doesn't mention.

API Pricing: Choosing Between Flare and Sunburst

Two API models launched at identical pricing: $8 per million image input tokens ($2 cached), $30 per million output tokens, and $5 per million text input tokens ($1.25 cached). GPT-Image-2.5 Flare is the default, tuned for speed and volume, social content, e-commerce shots, rapid prototyping. GPT-Image-2.5 Sunburst targets premium workflows needing tighter editing control, with longer generation times, suited to production-ready campaign creative. Inside the consumer ChatGPT app, usage is included in existing subscriptions with no extra charge, though rate limits still apply.

Safety: OpenAI Admits the Deepfake Risk Itself

The system card is candid about this: higher realism means higher deepfake risk. Measured unsafe-generation rates came in at 1.09% for Sunburst and 1.41% for Flare, both slightly better than Images 2.0's 1.64%, but not zero. Outputs carry C2PA metadata and an invisible watermark to help trace provenance later.

Should You Switch?

If you need fast, high-volume output and can tolerate some noise (social posts, drafts), Flare is worth switching to, the speed gain is genuine
For production or print work where image cleanliness matters, run a side-by-side test against your current pipeline before fully switching over
If Sketch-style rough-draft-to-reference workflows fit how you work, this is one of the more intuitive implementations on the market right now

You won't know until you try it. (好不好用，試了才知道)

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