FLUX 3
FLUX 3 is a multimodal foundation model that jointly learns from images, video, and audio within one unified architecture, building a representation of how objects hold together, how things move, and how events sound. Built on the Self-Flow approach, it aligns multimodal generation and understanding in the same backbone so each modality constrains the others, sound matches impact, motion follows physical properties, and future events follow from the past. FLUX 3 can mix modalities and jointly generate images, video, and native audio from text prompts or references such as images, video, and audio. Its video capabilities include text-to-video, image-to-video animation, video-to-video transformation, generative video-and-audio continuation, keyframe-controlled transitions, multilingual dialogue, animated typography, diverse styles and aspect ratios, and agentic chaining into longer multi-shot sequences.
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GPT-Image-2.5 Flare
GPT-Image-2.5 Flare is a hosted image-generation model available through the OpenAI API. It accepts text prompts and image inputs and produces image outputs. Developers can call it through the Images API to generate images or edit supplied images, or use it as an image-generation tool within Responses API workflows that support conversations and multiple steps. Requests can set image quality to low, medium, high, xhigh, max, or auto, and configure output size, format, and compression. OpenAI positions Flare for fast, everyday image generation, while its GPT-Image-2.5 Sunburst model is intended for workflows prioritizing precise editing. The model is designed for developers and organizations adding image creation or editing to their own applications. Access requires API credentials, and usage is billed by tokens, with rates depending on text or image input, image output, and standard or batch processing.
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MiniMax H3
MiniMax H3 is a general-purpose omni-modal generation model that jointly understands multimodal contexts spanning text, images, video, and audio. It generates videos with native stereo sound at up to 2K resolution and 15 seconds in length, delivering content for advertising, branding, ecommerce, product design, UI/UX, gaming, and creative workflows. Users can combine reference types in one instruction, for example, transferring camera movement from a video, placing a character from an image into the scene, and matching vocals from an audio clip, while describing the relationships in natural language. H3 supports text-to-image, text-to-video with jointly generated audio, multi-shot modeling, text-to-audio, and generalized reference and editing across images, videos, and audio. Voice, sound effects, and music are modeled together. The model excels at instruction following, accurate text and brand presentation, and video-to-video motion transfer.
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MAI Image 2.7
MAI Image 2.7 is Microsoft AI’s image-editing model for making targeted changes to existing images while preserving their broader composition. It can restyle or relight a scene, move objects into new settings, revise text and symbols in images, and restore or enhance visual assets. It is aimed at creators and others who need to refine images without rebuilding an entire scene. Preview access is available through MAI Playground, Arena, and Artificial Analysis. The initial preview focuses on image editing, with text-to-image generation planned for a later release. Example uses include changing a product scene, modifying an image’s mood, and making selective edits to individual objects.
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