MAI-Image-2.6 is a Microsoft AI closed-API image generation model. CompareLLM Images Estimated rating is 1820. Render latency averages 25.1s. MAI-Image-2.6 is an image generation and editing model from Microsoft AI, the precision tier of the MAI-Image-2.6 family alongside the faster [MAI-Image-2.6 Flash](/microsoft/mai-image-2.6-flash). It is suited for design-ready visuals and... Numbers below are dated snapshots from empirical benchmark harnesses.
Independent evaluation answering: "Is MAI-Image-2.6 the right model for your workload & budget?"
Image generation is a separate job from vision-language understanding.
Dated snapshot metrics aggregated from official evaluators and API providers with visual relative score bars.
Our Image generation list. Named third-party suites stay labelled as references, not this rating.
Accuracy in including multiple requested entities, spatial relations, styles, and negative prompts.
Legibility and spelling accuracy when generating words, logos, signs, and in-image lettering.
Compact class for how long one standard image takes. Exact seconds stay in the fact sheet.
Commercial API price per 1,000 standard 1024x1024 generated image assets.
Ecosystem support across HuggingFace Diffusers, ComfyUI, ControlNet, and LoRA fine-tuning.
| Benchmark Metric & Meaning | Reported Score & Capability Fill | CompareLLM Review |
|---|---|---|
Maximum output (tokens) Maximum Response Length | 1k tokens | Source not recorded · Sep 21, 2026Maximum completion tokens for one request on the same endpoint. |
Input token price Cost to Prompt (Input tokens) | $5/1M tok | Source not recorded · Sep 21, 2026Published text input price on the endpoint this sheet is read from. |
Context window (tokens) Context Window Capacity (tokens) | 4k tokens | Source not recorded · Sep 21, 2026Maximum input context on the same endpoint. |
Generation time Time to Make One Image | 15–30s | Source not recorded · Sep 21, 2026 |
Peers in the same closed API frontier image performance tier — not a jump to an unrelated frontier SKU.
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Compare MAI-Image-2.6 against
Models may use different benchmarks and test settings. This is an indicative composite, not a controlled head-to-head comparison or community Elo. Admin-approved sentiment estimates fill categories without accepted benchmark results. Estimates are labelled and do not increase benchmark coverage. Coverage refers to the configured recipe, not confidence.
Release recent-models-2026-09-23-r1 · recipe reported-text-2026-09-11-r1 · method reported-with-estimates-v2 · research through 2026-09-23
Overall benchmark coverage includes missing applicable categories. Estimated categories contribute to the rating but add no benchmark coverage.
Editorial estimate, anchored to the Artificial Analysis arena for this modality, where MAI-Image-2.6 scores 1147.14. Placed by where that sits between HiDream-O1-Image-1.5 at 1022 and GPT Image 2.5 Flare at 1188, the span the board published on 2026-09-21, mapped onto 62-88. Arena Elo is blind human preference, not this category's recipe, so this is an ordering anchor rather than a measurement, and it is never compared against another modality's board. Any accepted result that clears the evidence thresholds replaces it.
As of 2026-09-21 · review on 2026-12-21 · Editorial estimate (not a benchmark result)
Sentiment source 1 →What this model is available as, what it takes to run, and where its identity comes from.
The provider's deployment options have not been reviewed for this model.
mai-image-2.6microsoft/mai-image-2.6Concise empirical overview formatted for citations and prompt context

Google's Gemini 3.1 Flash Image generates at up to 4096x4096 and bills $67 per 1,000 images at a 9.1-second median. It ranks seventh on the image arena — below three OpenAI models costing three times more.

OpenAI holds the top two places on the image arena. It also charges twenty-one times what the eighth-placed model costs. Here is the full quality-versus-price ladder, with the numbers.
Plain-English methodology and leaderboard answers
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Plotted against all active catalog models (50th percentile = catalog median).
2 of 3 dimensions have ranking-eligible evidence. Missing axes are not converted to zero.
Ranks in the top tier (≥75th percentile) for Image generation.