Tasks and inputs
MAI-Image-2.6 is listed for Image-text-to-image, Text-to-image. It accepts text, image and produces image. Use the publisher’s input format and preprocessing for your chosen deployment.
MAI-Image-2.6 is Microsoft AI’s image model for visual creation; deployment access and billing depend on the selected product.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
MAI-Image-2.6 is listed in Microsoft AI’s current model family. Its role is image generation, so evaluate the delivered visual asset and the edits needed to make it usable. Product availability and an API deployment are separate questions; a catalog listing does not establish that every developer account can call it.
Use the model’s product page to establish the currently offered deployment. A generally available public API identifier, numeric context allowance and maximum output limit have not been established for this profile, so those fields remain empty. Do not construct an API name from the display name or transfer the limits of a neighboring model.
Record the product, account settings and model shown for each evaluation. Use your own representative inputs with explicit acceptance rules, and inspect the complete deliverable. No token or media rate is inferred from another Microsoft model. Check the selected service’s billing unit and access terms before estimating production usage.
Build a small evaluation set from the work your application actually handles. Include incomplete information, contradictory inputs and a case that should stop for clarification. Define an acceptable deliverable before running the model, then inspect failures as carefully as successful examples. Keep input material, tools and effort settings consistent when comparing candidates.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
Explore microsoft models, browse model tasks, or compare two models with the same acceptance criteria.
Compare the model on the work you need to complete.
MAI-Image-2.6 is listed for Image-text-to-image, Text-to-image. It accepts text, image and produces image. Use the publisher’s input format and preprocessing for your chosen deployment.
Choose the output size and quality your design needs. Include drafts and revisions when budgeting an accepted image.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
Alibaba
Qwen-Image-2.1-Turbo creates and edits images, including reference-guided and transparency workflows; hosted billing is separate from local deployment.
Alibaba
Qwen-Image-2.1-Pro creates and edits images, including reference-guided and transparency workflows; hosted billing is separate from local deployment.
Meta
Muse Image 1.0 generates and edits images through conversational or single-shot endpoints, with flat per-image Meta Model API billing.
krea
Krea 2 Raw: a base checkpoint for further training, not the recommended everyday inference release.
krea
Krea 2 Turbo: the post-trained and distilled Krea 2 checkpoint for image generation.
OpenAI
GPT-5.4 Image 2 from OpenAI: Image model for prompt-driven generation, editing, and visual design workflows.