Krea 3 vs Grok Imagine Image 2.0：一方のモデルにはEloがあり、もう一方にはストップウォッチがある

There is a head-to-head table you can build for K​rea 3 and Grok Imagine Image 2.0, and then there is the one that actually exists. Grok Imagine Image 2.0 has been measured: x​AI's editor, released 7 August 2026, sits at 1,110 Elo on the Artificial Analysis image-editing leaderboard — thirteenth of the ranked models, on 7,792 blind comparisons, at a listed $60 per 1,000 images. K​rea 3, released 15 October 2026, has been measured by nobody. It arrives with a vendor stopwatch — under 8 seconds per edit at native 2K for $0.06 — and no third-party number of any kind. So this is less a contest between two editors than a choice between two kinds of evidence.

その対比を成す両方とも真実であり、どちらかが他方を打ち消すこともない。Eloは、ラベルが見えないときに群衆が何を好むかを教えてくれるが、あなたのロゴが編集を生き延びたかどうかまでは教えてくれない。レイテンシの数値は、ベンダー自身のインフラがベンダー自身のプロンプトに対して何をしたかを教えてくれるが、モデルが優れているかどうかまでは教えてくれない。両者を併せて読むことだけが誠実な選び方であり、この記事の残りの部分もそうしている。

それぞれが何であるかを、ベンダー自身の言葉で

Grok Imagine Image 2.0 is positioned by x​AI as an editing environment rather than a one-shot generator, and its feature list reads like one: Magic Wand for region-level edits, segmentation for precise region selection, background removal, multi-image input, a Smart Resize that recomposes one image into nine aspect ratios by inventing new frame content rather than cropping, and templates for product photography, headshots, e-commerce listings, game assets and marketing posters. It is the default Quality Mode on grok.com/imagine and on mobile. The API additionally exposes aspect ratio — including 21:9 and 5:2, both new with 2.0 — resolution, and a low/medium/auto quality parameter.

K​rea 3 is narrower and stranger. It is an editor with no generator story attached: region-scoped changes in a drawn box, character consistency across a sequence, up to six references on the launch post and eight on the product page, native 2K, and a voice-note workflow in the app where you speak an instruction and get the edit back. Where G​rok ships named tools and presets for verticals, K​rea ships one mechanism — find the region, render only that — and a speed claim.

• Released — K​rea 3: 15 October 2026. Grok Imagine Image 2.0: 7 August 2026.

• Independent editing rank — K​rea 3: unranked, no entry. Grok Imagine Image 2.0: #13 at 1,110 Elo on 7,792 samples, per Artificial Analysis.

• Price — K​rea 3: $0.06 per image at 2K, $0.03 at 1K, flat. Grok Imagine Image 2.0: from $0.04 per image, billed at the quality tier actually served; the board's representative figure is $60 per 1,000.

• Speed — K​rea 3: under 8 seconds end to end at 2K, vendor-stated. Grok Imagine Image 2.0: no figure from x​AI and no independent measurement; the only seconds-per-edit number we can find for it is K​rea's own, at 19 seconds, which is a competitor's measurement on a competitor's traffic.

• Resize and reformat — K​rea 3: not a documented workflow; edits are region-scoped. Grok Imagine Image 2.0: Smart Resize across nine aspect ratios, recomposing rather than cropping.

• Multi-image input — K​rea 3: 6 or 8 depending which K​rea page you read. Grok Imagine Image 2.0: five source images per edit, per current documentation, up from the three the API capped at launch.

• 重み — どちらもなし。どちらの側にもオープンな重みはなく、両方ともホスト型モデルです。

十三の列を読む

Elo を扱うときの誘惑は、その数値を評決として扱ってしまうことだ。むしろ、どこで意見が分かれているかを示す地図として使うほうが有用だ。

On the Artificial Analysis image-editing board, Grok Imagine Image 2.0 sits at 1,110 Elo across 7,792 blind comparisons, listed at $60 per 1,000 images. For scale, the top of that same board is O​penAI's GPT Image 2.5 Sunburst at 1,198 on a stated interval of 1,187 to 1,209, its Flare sibling at 1,177, and a tie for third between Nano Banana 2.1 and M​icrosoft's MAI-Image-2.6 at 1,148. Those gaps are wide relative to the intervals — Sunburst to G​rok is 88 Elo — but they say nothing at all about latency, and G​rok's entry carries less than half of Sunburst's sample count.

Two caveats to hold. The board lists G​rok's creator as S​paceXAI, which is a housekeeping detail worth knowing before you search for the row and fail to find it. And the rank is board-specific in a way that matters here: the same model sits fifth on the text-to-image board at 1,166 Elo, and thirteenth on editing at 1,110. If you are buying an editor, the editing row is the one you are buying, and it is the lower of the two.

The sharper version of that comes from the tier it replaces. The older grok-imagine-image-quality slug still sits on the editing board at 1,091, nineteenth place, so on editing the new tier is ahead of the old one by roughly nineteen Elo, for a $0.01-per-image premium. On text-to-image the same generational step was worth well over a hundred. x​AI shipped a much better generator and a modestly better editor, and only one of those improvements would have led a launch post.

And G​rok's independent reputation to date is uneven in a specific way: in a six-prompt, single-seed comparison against gpt-image-2 we covered previously, x​AI's model led clearly on photorealism and identity retention — correct portrait anatomy, pore-level skin detail, natural catchlights — and lost on production-critical behaviour, rendering Traditional Chinese characters when asked for Simplified in a film-poster headline, and returning a photorealistic image with only a light painterly pass when a watercolour style fusion was requested. That is one small test, not a body of evidence, and we said so at the time. But the failure it found — multilingual text compliance — is the kind that takes a localisation pipeline down, and no Elo average will ever surface it.

K​rea 3 has no equivalent record in either direction. It is four days old, has no board entry, and the only third-party signal attached to it is a customer testimonial: Pixelcut's co-founder and CEO, quoted by K​rea, saying his team ran early checkpoints in front of paying users and that lighting on product shots was the standout. Useful, unverifiable at our end, and labelled here as a partner statement.

価格差よりも重要な機能差

表面上は価格が近い。6セントに対して、実際に提供される品質ティアに応じて上がる「$0.04から」。違いはセントではない。各モデルがあなたのフレームに対して何を厭わずに行うかだ。

Grok Imagine Image 2.0 will reformat. Smart Resize invents new content to turn one image into nine aspect ratios rather than cropping, which is exactly what an ad team needs when the same hero has to run at 1:1, 9:16 and 2:1. It will also composite up to five sources into one edit. K​rea 3 will not do either, as documented — its pitch is the opposite discipline. Draw a box, describe the change, and everything outside the box stays where it was, with precision defined as the share of pixels outside the edit area left unchanged, compared at quarter resolution after alignment.

Those are complementary, not competing, and the cost of choosing wrongly is asymmetric. A marketing team that buys K​rea 3 for a reformatting workflow gets a model that is excellent at a job it was not asked to do. A catalogue team that buys Grok Imagine Image 2.0 for label-accurate product edits gets a very capable editor with no published containment metric — and possible multilingual text risk on top, per that one test.

カタログ規模でのコスト、両方の注意点が付いた状態で

For K​rea 3 the arithmetic is trivial and the risk is that it is the only arithmetic available. 100,000 edits at $0.06 is $6,000, and K​rea's own FAQ says the launch price is the list price, not a subsidy, and that it expects the price to fall rather than rise. That is a vendor statement about the future, so a budget built on it is a bet.

For Grok Imagine Image 2.0 the shape is different, and there is a deadline hiding in it. The model bills from $0.04 per image at the quality tier actually served, and the default when you omit the parameter is auto — which currently serves low for generation and medium for editing, so the same request can bill differently depending on which path the service picks. Pinning the tier makes the bill predictable. Meanwhile the older grok-imagine-image-quality slug, at $0.05 per image, retires on 2 November 2026 after a 60-day notice; from that date it keeps resolving but requests are served by Grok Imagine Image 2.0 at low quality. Teams that change nothing see a price drop and a silent change in output quality, which is the worst of both — unless you read the model field in your responses. That retirement schedule is x​AI's own documentation, not something anyone has independently verified.

両方がどこに位置し、それらをどう保持するか

どちらのモデルも、今月、顧客向けパイプラインに直接組み込むべきものではない。一方にはリーダーボードの順位があり、その下には廃止されたスラッグがあり、多言語テキストの障害が文書化されている。もう一方には価格とストップウォッチしかなく、外部の証拠は一切ない。どちらについても妥当な姿勢は、フォールバックを用意したうえでの試験運用だ。

That is the specific thing routing buys you here, and it is worth being precise about what we do and do not cover. OrcaRouter provides one OpenAI-compatible endpoint across a few hundred models with provider list prices passed through at no markup — a vendor price cut reaches your bill the same day — plus failover that sends a provider error or rate limit to a fallback rather than into your batch. On availability: our catalogue carries x​AI's grok-imagine-image line and its model page is live, but the newest Grok Imagine Image 2.0 tier is a separate entry, so check the current model list rather than assuming the 2.0 quality mode is routable today. K​rea 3 is not routed by us at all. What the endpoint does cover is the rest of the comparison set — GPT Image 2 and the image models you would benchmark either of these against — so the test you should be running is one configuration, not three integrations.

証拠が偏っているとき、どう決断すべきか

今日、公開された群衆計測による品質順位を持つエディターが必要なら、それは Grok Imagine Image 2.0 です。そして、それが1位ではなく11位にランクされていること、固定しない限り請求額は品質ティアに応じて変動すること、スラッグ単位の移行には期限があることを承知のうえで導入してください。レスポンス内の model フィールドを読み、2026年11月2日より前に廃止予定の品質スラッグを移行してください。

If you need flat pricing, contained edits and the shortest wall-clock time anyone in this category has published, that is K​rea 3 — with the understanding that you are the first person testing it, that its reference count is documented two ways, and that its identifier appears as K​rea 3 Beta in K​rea's own plan tables.

決め手はモデルではない。あなたが許容できるのは、2つの失敗モードのどちらかだ。40秒かかり、ローカリゼーションであなたを驚かせる編集か、8秒で返ってきて、作り手以外の誰にも評価されたことがない編集か。自分の画像を40枚、両方に通し、答えはどちらのベンダーのものでもなく、あなた自身のものにしよう。

失敗モードがまだ文書化されていないモデルにとって、有用な対応物は、すでに他の場所で何がうまくいかなかったかの記録です。このクラスのモデルに関する文書化されたAIインシデントとエージェントの失敗は、以下に収集されています：OrcaRouter AI Incident Archive。各エントリには、独自の出典、深刻度、信頼度グレード、係争フラグが付いています。