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GPT Image 2 對 Nano Banana：2026 基準測試點揀？

純文字生成圖片榜單方面，Artificial Analysis 將 GPT Image 2（high）列第一，Elo 1331；呢個係目前最清晰嘅公開領先訊號 [31]。 改圖未見壓倒性勝負：Artificial Analysis 顯示 GPT Image 2 係 1251 Elo，Nano Banana Pro 係 1250 Elo，只差 1 分 [30]。

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Editorial comparison graphic for GPT Image 2 versus Nano Banana AI image generation benchmarks
GPT Image 2 vsGPT Image 2 leads the available text-to-image benchmark signal, while Nano Banana remains a strong workflow choice for Gemini-native and high-resolution use cases.
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Create a landscape editorial hero image for this Studio Global article: GPT Image 2 vs. Nano Banana Benchmarks: Which AI Image Model Wins in 2026?. Article summary: GPT Image 2 is the benchmark favorite for text to image: Artificial Analysis lists GPT Image 2 (high) first at 1331 Elo.. Topic tags: ai, image generation, openai, google, gemini. Reference image context from search candidates: Reference image 1: visual subject "# 2026 AI Image API Benchmark: GPT Image 2 vs Nano Banana 2/Pro vs Seedream 5.0. Generative AI is no longer judged solely by aesthetic appeal, but by **API reliability, text-render" source context "GPT Image 2 vs Nano Banana 2/Pro vs Seedream 5.0 - Atlas Cloud" Reference image 2: visual subject "GPT Image 2 leads in spatial logic and 99.2% text accuracy, while Nano Banana 2 excels in 4K production speed and real-time search." source context "GPT Image 2 vs. Nano Banan

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結論先講：GPT Image 2 係 2026 年呢組證據入面較清晰嘅 benchmark 贏家，尤其係 text-to-image。之不過，揀模型唔應該只睇榜單第一名。實際工作流入面，Nano Banana 仍然係好有競爭力嘅選擇，特別係你已經用緊 Gemini 工具鏈、需要文件寫明嘅高解像輸出、要快手出多個版本，或者成本敏感。

快速判斷：你應該先試邊個？

你最關心現有證據點講實際建議
純文字生成圖片質素Artificial Analysis 嘅 Text to Image Arena 將 **GPT Image 2（high）**列第一，Elo 1331 [31]。如果你只想揀一個 benchmark 上最有優勢嘅 text-to-image 模型，先試 GPT Image 2。
改圖能力Artificial Analysis 改圖榜顯示 GPT Image 1.5 係 1267 Elo 第一，GPT Image 2 係 1251，Nano Banana Pro 係 1250 [30]。GPT Image 2 同 Nano Banana Pro 太接近；用你自己嘅素材、mask、reference image 實測。
4K API 輸出Google Nano Banana 文件列出可選解像度包括 512、1K、2K、4K [35]。如果「API 要明確支援 4K」係硬性規格，Nano Banana 比較易用文件核實。
官方價格透明度OpenAI 價格頁列出 GPT-image-2 嘅 image input、cached input、image output、text input 等 token 價格 [14]。以呢批來源計，GPT Image 2 較容易即時計預算。
圖入面要有準確文字第三方比較指出，當圖片內文字、複雜版面、多重限制或一致性重要時，GPT-image-2 較合適 [6]。廣告圖、poster、標籤、UI mockup、圖解、包裝，先用 GPT Image 2。
快速試稿同大量變體Google Skills 形容 Gemini 2.5 Flash Image（即 Nano Banana）支援高速圖片生成、prompt 改圖同視覺推理 [43]。做草稿、方向探索、Gemini 原生 app，Nano Banana 仍然好順手。

最大重點：text-to-image 係 GPT Image 2 領先

今次最乾淨嘅公開榜單訊號，來自 Artificial Analysis。佢嘅 Text to Image Arena 片段顯示，**GPT Image 2（high）**以 1331 Elo 排第一，喺可見排名入面高過 GPT Image 1.5 同 Nano Banana 2 [31]。

所以，如果問題只係：「邊個模型喺公開 text-to-image benchmark 訊號較強？」答案係 GPT Image 2。

不過，Elo 榜唔等於宇宙真理。佢反映嘅係某一套評測設計、某個模型版本、某批 prompt，同人類偏好投票。模型更新、prompt 寫法、抽樣設定一變，排名都可以郁。

其他報道大方向都偏向 GPT Image 2。Neurohive 指 GPT Image 2 按 LM Arena 資訊喺多個圖片生成類別取得第一，並聲稱較最近競爭者領先 +242 Elo [16]。CalcPro 亦報道 GPT Image 2 text-to-image 分數為 1512，並指較 Nano Banana 2 領先 +242 Elo [28]。不過，若要用較保守、適合採購或技術決策嘅講法，最好仍然落喺可見榜單片段：Artificial Analysis 顯示 GPT Image 2 以 1331 Elo 領先 text-to-image 榜 [31]。

改圖：唔好講到一面倒

改圖方面，現有證據唔支持「GPT Image 2 完全碾壓 Nano Banana」呢種講法。

Artificial Analysis 圖像編輯榜片段顯示，GPT Image 1.5（high）以 1267 Elo 排第一，GPT Image 2（high）以 1251 排第二，Nano Banana Pro（Gemini 3 Pro Image）以 1250 排第三 [30]。GPT Image 2 同 Nano Banana Pro 只差 1 Elo，單憑呢個片段，唔應該當成決定性勝利。

Arena.ai 圖像編輯榜片段亦顯示 

gemini-2.5-flash-image-preview (nano-banana)
有 1300±3 Elo；不過，該可見片段未有喺同一段排名範圍顯示 GPT Image 2，所以只能支持「Nano Banana 喺改圖 arena 有競爭力」呢個較窄結論，唔足以直接排定佢同 GPT Image 2 邊個高 [29]。

實務建議好簡單：如果你主要做改圖，唔好只睇總榜。用你自己嘅產品相、人像、設計稿、mask、reference image 同修改 prompt，兩邊各跑一輪。

名字有啲亂，尤其係 Nano Banana

GPT Image 2 喺來源入面相對清楚。OpenAI 開發者文件列出模型為 gpt-image-2-2026-04-21，亦顯示 API 使用嘅分層 rate limits [13]。OpenAI 價格頁則列出 GPT-image-2 作為圖像生成模型，並提供 image input、cached image input、image output、text input、cached text input 等 token-based 價格 [14]。

Nano Banana 呢個名就比較多變。Google 圖像生成文件以 Gemini API 呈現 Nano Banana image generation，示例程式碼入面見到 gemini-3.1-flash-image-preview [35]。Google Skills 又將 Gemini 2.5 Flash Image 稱為 Nano Banana，定位係高速圖片生成、prompt-based editing 同 visual reasoning [43]。Artificial Analysis 改圖榜亦用到另一個相關名稱：Nano Banana Pro，並標示為 Gemini 3 Pro Image [30]。

呢點唔係吹毛求疵。你見到「Nano Banana 2」、「Nano Banana Pro」、「Gemini 2.5 Flash Image」或者「Gemini 3.1 Flash Image Preview」嘅 benchmark，未必量度緊同一條 API route 或同一個模型版本。做正式比較時，要記低精確模型名、API route、測試日期、解像度同設定。

乜情況先揀 GPT Image 2？

GPT Image 2 最適合用喺「錯咗之後好麻煩」嘅任務。Analytics Vidhya 嘅比較指出，當圖片內文字必須正確、prompt 涉及多重限制或版面、又或者輸出一致性重要時，GPT-image-2 較合理 [6]。另一個 hands-on 比較亦用一句幾貼地嘅說法總結：GPT 贏喺「每一個字都重要」嘅場景；Nano Banana 贏喺「每一粒光影像素都重要」嘅場景 [3]。

你可以先用 GPT Image 2 做：

  • 有指定 headline、call to action 嘅廣告創意。
  • Poster、餐牌、指示牌、產品標籤。
  • UI mockup、app screen、網站圖像，尤其係要有可讀介面文字。
  • 教學圖、流程圖、infographic、帶標註嘅 diagram。
  • 產品包裝、品牌素材，特別係文字準確度會影響交付。
  • 有好多物件、空間關係、版面規則嘅複雜 prompt。

呢唔代表 Nano Banana 做唔到。只係按目前 benchmark 同比較證據，GPT Image 2 對文字準確、結構化版面、複雜指令跟從，有較強嘅第一測試理由 [6][31]。

Nano Banana 仍然值得用喺邊度？

Nano Banana 喺呢批來源入面最強嘅優勢，唔係單一榜單冠軍，而係工作流貼合度。

Google Nano Banana 文件列出多個 aspect ratio，並有 resolution 設定，可選 512、1K、2K、4K [35]。如果你嘅產品規格寫明要有官方文件可核實嘅 4K generation path，喺呢批來源入面，Google 文件比 OpenAI 片段更易直接確認。

另外，Nano Banana 亦明顯偏向速度同迭代。Google Skills 形容 Gemini 2.5 Flash Image／Nano Banana 支援高速圖片生成、prompt-based editing 同 visual reasoning [43]。一篇 hands-on 比較得出嘅結果亦比「榜單大勝」敘事接近得多：2 項 GPT 贏、2 項 Nano Banana 贏、2 項打和 [3]。

你可以先用 Nano Banana 做：

  • 已經建喺 Gemini、Google AI Studio 或 Google developer tooling 上嘅應用 [35][43]。
  • 需要透過示例 Gemini API path 使用文件列明嘅 512、1K、2K 或 4K 輸出 [35]。
  • 大量草稿、variant、概念探索圖。
  • 光線、質感、整體真實感比圖片內文字更重要嘅畫面 [3]。
  • 成本係重大考慮；但第三方成本說法要再對照最新官方帳單頁同實際 route 驗證 [6]。

價錢同 rate limit：官方來源實際見到啲乜？

OpenAI GPT-image-2 嘅價格喺提供來源入面較清楚。OpenAI 價格頁列出：image input 每 100 萬 tokens US$8、cached image input 每 100 萬 tokens US$2、image output 每 100 萬 tokens US$30、text input 每 100 萬 tokens US$5、cached text input 每 100 萬 tokens US$1.25 [14]。

OpenAI GPT Image 2 模型頁亦顯示分層 rate limits。可見片段入面，Free 不支援；Tier 1 為 100,000 TPM、5 IPM；Tier 5 達 8,000,000 TPM、250 IPM [13]。

至於 Nano Banana，提供嘅 Google 官方圖像生成片段確認咗 Gemini API route、aspect ratio 同解像度選項，但未見到可以直接同 OpenAI 對照嘅價格表 [35]。Analytics Vidhya 指 Nano Banana 2 在大規模使用、尤其 batch processing 時成本明顯較低 [6]；但呢個係第三方比較說法。真正落 production 前，仍然要核實準確 Google model variant、API route、解像度、batch mode 同最新 billing page。

如果你要自己測，點先公平？

公開榜單有用，但圖像生成非常食 prompt。一篇 hands-on 比較指出，prompt 質素可以令 GPT Image 2 提升一整個等級；喺某些測試入面，呢個差距甚至大過模型之間嘅差異 [3]。

比較兩個模型時，建議至少做到：

  1. 同一批 prompt、同一批 reference image。 唔好用精修過嘅 GPT prompt 去對一條隨手寫嘅 Nano Banana prompt。
  2. 拆開評分。 文字準確、prompt adherence、構圖、photorealism、改圖質素、延遲、成本，要分開計。
  3. 放入真實 production 限制。 包括 aspect ratio、解像度、throughput、rate limit、預算假設 [13][14][35]。
  4. 記低模型名同日期。 你測嘅係 GPT Image 2、Nano Banana 2、Nano Banana Pro、Gemini Flash Image，定另一條 route？來源入面啲名稱本身已經有變化 [30][35][43]。
  5. 可以就 blind review。 評審知道邊張圖由邊個模型出，偏好可能會改變。

2026 最實際結論

如果你要一句 benchmark verdict：揀 GPT Image 2。Artificial Analysis 將 GPT Image 2（high）列為 text-to-image 第一，Elo 1331 [31]。對文字密集、版面敏感、指令複雜嘅圖片生成，佢係較合理嘅第一選擇。

但如果你係為產品或團隊設計 production setup，就唔應該所有圖都只丟畀一個模型。比較穩陣嘅做法係：

  • GPT Image 2：處理精準文字、招牌、UI screen、diagram、包裝、複雜版面。
  • Nano Banana：處理 Gemini 原生 app、文件列明 4K 選項嘅高解像流程、快速視覺探索，以及可以後期再加字或修字嘅圖片 [35][43]。

一句收尾：GPT Image 2 贏咗 benchmark 標題；Nano Banana 仍然贏到唔少真實工作流。

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重點

  • 純文字生成圖片榜單方面，Artificial Analysis 將 GPT Image 2（high）列第一，Elo 1331；呢個係目前最清晰嘅公開領先訊號 [31]。
  • 改圖未見壓倒性勝負：Artificial Analysis 顯示 GPT Image 2 係 1251 Elo，Nano Banana Pro 係 1250 Elo，只差 1 分 [30]。
  • 要精準文字、複雜版面、海報、UI mockup、包裝同圖表，先試 GPT Image 2；要 Gemini 原生流程、文件列明 512 至 4K 輸出、快速迭代，Nano Banana 仍然好實際 [6][35][43]。

人們還問

「GPT Image 2 對 Nano Banana：2026 基準測試點揀？」的簡短答案是什麼？

純文字生成圖片榜單方面，Artificial Analysis 將 GPT Image 2（high）列第一，Elo 1331；呢個係目前最清晰嘅公開領先訊號 [31]。

首先要驗證的關鍵點是什麼？

純文字生成圖片榜單方面，Artificial Analysis 將 GPT Image 2（high）列第一，Elo 1331；呢個係目前最清晰嘅公開領先訊號 [31]。 改圖未見壓倒性勝負：Artificial Analysis 顯示 GPT Image 2 係 1251 Elo，Nano Banana Pro 係 1250 Elo，只差 1 分 [30]。

接下來在實務上我該做什麼？

要精準文字、複雜版面、海報、UI mockup、包裝同圖表，先試 GPT Image 2；要 Gemini 原生流程、文件列明 512 至 4K 輸出、快速迭代，Nano Banana 仍然好實際 [6][35][43]。

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Search for GPT Image 2 vs. Nano Banana benchmarks and compare them as comprehensively as possible.

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引用的答案

GPT Image 2 appears to be the stronger benchmark leader, especially for prompt following, text-in-image, spatial reasoning, and edits, while Nano Banana is the better default when speed, cost, Gemini integration, and high-resolution/4K workflow matter more. The evidence is uneven: official docs confirm model availability/features, but many “benchmark” numbers come from third-party arenas or SEO-style comparison posts, so treat exact Elo gaps and category scores as directional rather than definitive.

Key benchmark takeaways

  • GPT Image 2 is listed in OpenAI’s API docs as gpt-image-2-2026-04-21, confirming it is an API model with documented rate limits and access controls [1].

  • Google’s official Nano Banana image-generation docs show support for multiple aspect ratios and selectable resolutions including 512, 1K, 2K, and 4K [2].

  • Third-party benchmark reports generally rank GPT Image 2 above Nano Banana/Nano Banana 2 in overall image-generation quality, with one Arena-related report claiming GPT Image 2 reached about 1512 Elo and led Nano Banana 2 by 242 points in text-to-image [13].

  • Artificial Analysis has a dedicated GPT Image 2 model page comparing quality, generation time, and price against other image models including Nano Banana, but the search result did not expose enough numeric details to independently verify all scores [11].

  • A hands-on comparison found a much closer result: 2 GPT wins, 2 Nano Banana wins, and 2 ties, summarizing GPT as better when “every character matters” and Nano Banana as better when “every pixel of light matters” [9].

Comparison table

DimensionGPT Image 2Nano Banana / Nano Banana 2Practical winner
Overall arena rankingReported as #1 in some third-party image arenas, with a claimed 1512 Elo and large lead over Nano Banana 2 [13]Reported as #2 in the same comparison, around 1360 Elo in one source [13]GPT Image 2, but verify live leaderboards
Text renderingMultiple comparisons say GPT Image 2 leads on text accuracy and layout-heavy outputs [10][14]Often described as improved but weaker for exact text and multi-constraint typography [9][14]GPT Image 2
Prompt adherenceGPT Image 2 is repeatedly described as stronger on complex constraints, spatial logic, and multi-object instructions [10][14]Nano Banana is competitive for simpler creative prompts and fast production tasks [9]GPT Image 2
Photorealism / lightingHands-on comparison says Nano Banana wins where lighting and pixel-level aesthetics matter [9]Nano Banana is often praised for realism, speed, and polished visuals [9]Nano Banana, depending on prompt
EditingArena-related snippets say GPT Image 2 scored highly on single-image edit tasks [13]Nano Banana is widely positioned as strong for editing and image-grounded workflows, but exact benchmark evidence is thinner in the available results [2][15]Slight GPT Image 2 on benchmark claims; Nano Banana for workflow
ResolutionOpenAI pricing/docs confirm GPT Image 2 exists, but search snippets did not expose a complete official resolution matrix [1][3]Google’s official docs show Nano Banana supports 512, 1K, 2K, and 4K outputs [2]Nano Banana for explicit 4K support
SpeedSome comparison posts claim Nano Banana is faster and more production-efficient [9][14]Official Google docs confirm generation API support but not benchmark speed in the search snippet [2]Nano Banana, based on third-party reports
CostOpenAI’s pricing page lists GPT-image-2 as “state-of-the-art” and gives token-based image pricing categories, but the snippet does not expose full per-image costs [3]Third-party sources claim Nano Banana/Nano Banana Pro can be materially cheaper per image, but exact figures vary across posts [5][14]Likely Nano Banana, but confirm current API pricing
EcosystemGPT Image 2 fits OpenAI/ChatGPT workflows and API usage [1][3]Nano Banana fits Gemini API, Google AI Studio, and Vertex-style workflows [2]Depends on stack

Where GPT Image 2 seems better

  • Use GPT Image 2 when the output must obey complicated instructions, object placement, scene logic, or precise layout constraints, because multiple comparisons describe it as stronger on spatial logic and multi-constraint prompts [10][14].

  • Use GPT Image 2 for images containing readable text, signs, UI mockups, labels, packaging, diagrams, or posters, because comparison posts consistently identify text rendering as a major GPT Image 2 advantage [10][14].

  • Use GPT Image 2 when you care most about benchmark rank, since third-party arena-style sources place it above Nano Banana 2 and report a large Elo lead [13].

Where Nano Banana seems better

  • Use Nano Banana when you need explicit 4K output support through Google’s documented image-generation API, because Google’s docs list selectable output resolutions including 4K [2].

  • Use Nano Banana when speed and cost matter more than maximum instruction fidelity, because third-party comparisons repeatedly position it as faster and more cost-efficient than GPT Image 2 [9][14].

  • Use Nano Banana if your workflow already lives in Gemini, Google AI Studio, or Google’s developer tooling, because Google documents Nano Banana image generation directly in the Gemini API docs [2].

Evidence quality and caveats

  • The strongest sources are the official OpenAI and Google docs for model availability, API support, pricing categories, aspect ratios, and resolutions [1][2][3].

  • The weakest evidence is exact “winner” scoring from SEO-style comparison blogs, because many publish benchmark tables without transparent prompt sets, sample sizes, or reproducible methodology [10][13][14].

  • Arena-style human-preference scores are useful for directional quality, but they can shift quickly as models update, prompts differ, and leaderboards separate text-to-image, editing, and multimodal tasks [8][11][13].

  • Insufficient evidence is available from the search results to state a fully verified, reproducible benchmark suite covering all categories such as typography, photorealism, character consistency, editing, latency, cost, and safety under one methodology.

Practical recommendation

  • Pick GPT Image 2 for: ad creatives with exact copy, infographics, product mockups, UI screenshots, diagrams, posters, multi-object layouts, and prompts where mistakes in text or relationships are unacceptable.

  • Pick Nano Banana for: high-throughput generation, 4K-oriented workflows, quick visual ideation, Gemini-integrated apps, lower-cost production, and photorealistic or lighting-heavy images where exact text is less important.

  • Best production strategy: route difficult text/layout/edit prompts to GPT Image 2, and route bulk, fast, high-resolution, or cost-sensitive prompts to Nano Banana.

來源

  • [3] GPT Image 2 vs Nano Banana 2: Hands-On 2026 Comparisongenspark.ai

    Net: 2 GPT wins, 2 Nano Banana wins, 2 ties. A much tighter picture than the framing you'll see elsewhere. The mental model that holds up: GPT wins where every character matters. Nano Banana wins where every pixel of light matters. Most real work sits somew...

  • [6] Is GPT Image 2 the Best Image Generation Model? - Analytics Vidhyaanalyticsvidhya.com

    At scale, Nano Banana 2 is significantly cheaper, especially with batch processing. gpt-image-2 makes sense when: Text inside images must be correct Prompts involve multiple constraints or layouts Output consistency matters Otherwise, Nano Banana 2 is the m...

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