MAI-Image-2.5-Pro vs GPT Image 2: The Image Crown Is Now Split

The cleanest way to summarize MAI-Image-2.5-Pro versus GPT Image 2 is that "best image model" stopped being one question. On Artificial Analysis's Image Editing Arena, Microsoft's MAI-Image-2.5-Pro is No. 1 at Elo 1,272; on the same site's Text-to-Image Arena, Ope​nAI's GPT Image 2 is No. 1 at Elo 1,369; and on the other big board — LMArena, now Arena — GPT Image 2 still dominates image editing outright, leading all seven prompt categories. Both models are premium, both are token-metered hosted APIs, and the honest answer to "which wins" depends entirely on which task you name: editing favors Microsoft's newcomer, generation and complex-prompt adherence favor Ope​nAI's incumbent.

The leaderboard split, read carefully

• Editing (Artificial Analysis): MAI-Image-2.5-Pro No. 1 — 1,272 Elo, ~6,100 samples. GPT Image 2 (high) No. 4 — 1,256 Elo.

• Text-to-image (Artificial Analysis): GPT Image 2 (high) No. 1 — 1,369 Elo, ~14,500 samples. MAI-Image-2.5-Pro No. 7 — 1,292 Elo, ~11,500 samples.

• Editing (Arena): GPT Image 2 leads at ~1,463 Elo with the largest measured lead in every category — the strongest independent result either model has.

The conflicting editing boards are not a contradiction; they are two different arenas with different model entries and different voter pools. Artificial Analysis tests the specific "high" tier of GPT Image 2 head-to-head against MAI-Image-2.5-Pro's preview build, and Microsoft's model wins there. Arena tests the medium build against a wider field, and Ope​nAI wins there by a wider margin. Both are real, both are independent, and neither board's lead is large enough to call the editing title settled.

What each one is good at

MAI-Image-2.5-Pro is a specialist editor. Microsoft built it for precise, surgical changes — swap an object, update in-image text, clean up artifacts — while keeping the rest of the image consistent, and its 94% multi-image character-consistency claim (vendor-reported) is the design goal in a number. Its headline capability is text rendering: Microsoft claims 96.8% accuracy across English, Chinese, Japanese, Korean, and Spanish, though the same docs cap output near a megapixel, so the "8K" phrasing on that claim is marketing to ignore. What the model is not is a blank-canvas leader: its #7 text-to-image rank says so directly.

GPT Image 2 is a generalist with a reasoning engine. It was the first Ope​nAI image model with a built-in thinking mode — it plans the layout, can search the web for references, and self-checks before drawing — which is why it is the acknowledged leader on complex, multi-constraint prompts and on Arena's editing categories. It renders multilingual text well (including CJK), supports up to 4K resolution with a 3:1 aspect-ratio ceiling, and ships three quality tiers. Its weaknesses are the mirror of its strengths: it is expensive at high quality, and it regenerates rather than surgically preserving — the "edit" is more like "re-render following this instruction," which is where MAI-Image-2.5-Pro's consistency pitch tries to differentiate.

Price

Both are token-metered, and neither publishes tokens-per-image, so per-image figures are conversions, not quotes.

• MAI-Image-2.5-Pro — $5 per million text-input tokens, $8 per million image-input tokens, $106 per million image-output tokens. Artificial Analysis's conversion: ≈ $108.50 per 1,000 1024×1024 images.

• GPT Image 2 — $5 per million text-input, $8 per million image-input, $30 per million image-output tokens. Per-image cost swings with the quality tier: roughly $0.006 low, $0.05 medium, $0.21 high at 1024×1024 — ≈ $211 per 1,000 at high quality.

So at the tiers buyers actually use, MAI-Image-2.5-Pro is roughly half the per-image price of GPT Image 2 high — a real delta at volume, and consistent with Microsoft's own (vendor-reported, scenario-specific) claim of up to 84% lower GPU cost than G​PT models in PowerPoint and OneDrive. The caveat: the leaderboard shows the "high" tier of GPT Image 2, and if you drop GPT Image 2 to medium quality its price falls near MAI-Image-2.5-Pro's while its Elo drops too.

Resolution and formats

• Output cap: MAI-Image-2.5-Pro is bounded near 1 megapixel (1024×1024-equivalent, minimum side 768px) — fine for web and most product visuals, a hard stop for print. GPT Image 2 goes to 4K (max edge 4,000px, total pixels up to ~8.3M) with a 3:1 aspect-ratio ceiling.

• Inputs: both accept JPEG/PNG images plus text. MAI-Image-2.5-Pro documents a 32k-token text input and a 131k context window; GPT Image 2's reasoning mode is the differentiator on the input side.

• Formats: GPT Image 2 does not support transparent backgrounds at launch; Microsoft's transparency story for the Pro tier is unstated either way.

If your output needs to be large — posters, print, billboards — GPT Image 2's 4K ceiling is a decisive advantage today. If your output is web-native, the megapixel cap is rarely the binding constraint.

Availability and the routing angle

Both are hosted APIs, but they are not equally reachable. GPT Image 2 has been generally available since 21 April 2026 through Ope​nAI's API and is routable through OrcaRouter today — one key, provider list price passed through at 0% markup, automatic failover across providers. MAI-Image-2.5-Pro is a 23 July 2026 public preview on Microsoft Foundry and the MAI Playground; it is not yet reachable through a third-party routing layer, and its preview pricing can move at GA.

That asymmetry is worth a decision note for anyone comparing these two in a real pipeline. You can route a slice of traffic to GPT Image 2 and a slice to another model on the same endpoint today, and swap the model string when Microsoft's preview becomes broadly callable. The workflow you want — compare both editors on your own images, keep the proven one as the fallback while the new one earns trust — is precisely what a routing layer gives you, and it costs nothing extra on OrcaRouter because the provider price is the price.

The verdict

If your task is editing existing images and your output is web-sized, MAI-Image-2.5-Pro is the value pick and the current independent #1 on Artificial Analysis's editing board — at roughly half the per-image price of GPT Image 2 high. If your task is blank-canvas generation, complex multi-constraint prompts, or large-format output, GPT Image 2 is the better tool and its #1 text-to-image rank and Arena editing dominance say so. They are both premium models and both worth having available; the split board is not a marketing tie — it is two genuinely different specialties. And because both are hosted, the routing layer is the sane way to run them side by side on your own images before you commit a production path to either.