VioEvo Integrations

Sunburst, part of the GPT-Image-2.5 series, is an adaptable model for creating and editing images, accessible through the OpenAI API. Developers can input both text prompts and images to either generate new visuals or alter current ones, with quality settings that vary from basic to high-end. This model is particularly suited for projects that demand precise modifications, such as promotional materials and top-tier product imagery. Users can access it through the Images API for seamless image generation and editing, or implement it as the visual creation element in the Responses API. Teams have the option to embed it into their products, creative applications, and automated visual workflows. Billing is structured around token usage, with separate rates for text and image inputs as well as the generated outputs; additionally, more economical rates are offered for batch processing and reused inputs. Utilizing this model allows developers to elevate their creative initiatives with high-quality visual content that meets their unique specifications, thereby enriching the overall user experience. Moreover, the flexibility of integration means that it can adapt to various industries and creative needs, making it a valuable tool for innovation.

Flare, a model for image generation, is made available through the OpenAI API, enabling users to create images based on text descriptions or existing visuals. Developers can leverage the Images API to either generate new images or enhance current ones, integrating it seamlessly into Response API workflows for enriched interactions and multi-step processes. Users can select from a range of image quality options, such as low, medium, high, xhigh, max, or auto, while also having the ability to fine-tune aspects like output dimensions, format, and compression levels. OpenAI promotes Flare as an efficient solution for rapid image generation, setting it apart from the more meticulous editing capabilities offered by its counterpart, the Sunburst model. Targeting developers and companies that wish to embed image creation or editing features into their software, access to Flare requires valid API credentials. Moreover, the service employs a token-based billing structure, where costs differ depending on the nature of the text or image inputs, the outputs generated, and whether standard or batch processing is selected, thus accommodating a variety of user needs. This model is a pivotal step towards enhancing the accessibility and efficiency of image generation for diverse applications, making it a valuable tool in the realm of creative technology. With its versatility and user-friendly approach, Flare is poised to become a go-to resource for businesses aiming to elevate their visual content creation.

Veo 3.1 builds on the capabilities of its earlier version, enabling the production of longer, more versatile AI-generated videos. This enhanced release allows users to create videos with multiple shots driven by diverse prompts, generate sequences from three reference images, and seamlessly integrate frames that transition between a beginning and an ending image while keeping audio perfectly in sync. One of the standout features is the scene extension function, which lets users extend the final second of a clip by up to a full minute of newly generated visuals and sound. Additionally, Veo 3.1 comes equipped with advanced editing tools to modify lighting and shadow effects, boosting realism and ensuring consistency throughout the footage, as well as sophisticated object removal methods that skillfully rebuild backgrounds to eliminate any unwanted distractions. These enhancements make Veo 3.1 more accurate in adhering to user prompts, offering a more cinematic feel and a wider range of capabilities compared to tools aimed at shorter content. Moreover, developers can conveniently access Veo 3.1 through the Gemini API or the Flow tool, both of which are tailored to improve professional video production processes. This latest version not only sharpens the creative workflow but also paves the way for groundbreaking developments in video content creation, ultimately transforming how creators engage with their audience. With its user-friendly interface and powerful features, Veo 3.1 is set to revolutionize the landscape of digital storytelling.

Grok Imagine is an AI-powered creative platform built to generate images and videos from natural language prompts. It allows users to quickly visualize ideas and concepts without relying on traditional design or video editing software. Grok Imagine supports a wide range of visual styles, from realistic imagery to artistic and conceptual designs, as well as short-form video content. The platform is designed for ease of use, making image and video generation accessible to users of all skill levels. Grok Imagine enables rapid iteration, allowing creators to experiment with scenes, motion, and composition. It is suitable for marketing assets, presentations, social media, and creative storytelling. The AI interprets prompts with contextual understanding to produce coherent visuals and smooth motion outputs. Grok Imagine accelerates creative workflows by removing technical barriers. Its fast output supports brainstorming and concept validation. The platform encourages creative experimentation across both static and dynamic media. Grok Imagine fits naturally into modern AI-assisted content creation pipelines. It provides an efficient way to turn imagination into visual and video reality.

Nano Banana 2.1 is a Google AI model for high-efficiency image generation, conversational image editing, and multimodal visual workflows. Released on October 6, 2026, it replaces Nano Banana 2 as Google's recommended model for new projects requiring a balance of image quality, speed, and cost efficiency. The model retains Flash-level performance while improving visual quality, rendered text, and consistency across successive image-editing turns. It supports text-to-image generation and conversational editing, allowing users to create visuals and then refine them through additional natural-language instructions. Images can be generated at 1K, 2K, or 4K resolution across numerous aspect ratios, including square, portrait, landscape, ultrawide, and unusually tall or wide formats. Advanced text rendering helps the model produce legible and stylized typography for applications such as diagrams, menus, infographics, advertising, and other marketing materials. Nano Banana 2.1 supports multi-reference generation with character resemblance for up to four people and high-fidelity representation of up to 10 referenced objects in a workflow. Its Google Search grounding capabilities can retrieve current information from the web, while Google Image Search grounding can provide additional visual references for generating factually or visually grounded images. The model also accepts video as multimodal context, analyzing frames and key events to create new images such as video thumbnails, cinematic posters, summary graphics, and artwork inspired by video content. Google describes Nano Banana 2.1 as the primary high-efficiency workhorse in its current image model lineup, while Nano Banana Pro remains positioned for more complex professional workflows requiring maximum world knowledge, localization, brand consistency, and creative control.

Nano Banana 2, officially known as Gemini 3.1 Flash Image, is Google DeepMind’s next-generation image generation model that combines Pro-level intelligence with ultra-fast performance. It integrates the advanced reasoning and world knowledge previously available only in Nano Banana Pro with the speed of Gemini Flash. The model draws on real-time web search data to enhance subject accuracy and contextual rendering. This enables users to create infographics, diagrams, marketing visuals, and data-driven imagery with greater factual grounding. Precision text rendering and multilingual translation capabilities allow for clean, legible designs across global markets. Improved instruction following ensures detailed prompts are executed faithfully, even in complex or multi-step creative tasks. Nano Banana 2 maintains subject consistency for up to five characters and numerous objects within a single project, supporting narrative and storyboard creation. It delivers production-ready assets with customizable aspect ratios and resolutions ranging from standard formats to 4K. Enhanced visual fidelity provides richer textures, improved lighting, and sharper details without sacrificing speed. The model is integrated across Google products, including the Gemini app, Search AI Mode, AI Studio, Vertex AI, Flow, and Ads. It also incorporates robust provenance tools such as SynthID and C2PA Content Credentials to support responsible AI transparency. By uniting intelligence, speed, quality, and accountability, Nano Banana 2 sets a new standard for accessible, high-performance image generation.

Kling 3.0 is a powerful AI-driven video generation model built to deliver realistic, cinematic visuals from simple text or image prompts. It produces smoother motion and sharper detail, creating scenes that feel natural and immersive. Advanced physics modeling ensures believable interactions and lifelike movement within generated videos. Kling 3.0 maintains strong character consistency, preserving facial features, expressions, and identities across sequences. The model’s enhanced prompt understanding allows creators to design complex narratives with accurate camera motion and transitions. High-resolution output support makes the videos suitable for commercial and professional distribution. Faster rendering speeds reduce production bottlenecks and accelerate creative workflows. Kling 3.0 lowers the barrier to high-quality video creation by eliminating traditional filming requirements. It empowers creators to experiment freely with visual storytelling concepts. The platform is adaptable for marketing, entertainment, and digital media production. Teams can iterate quickly without sacrificing visual quality. Kling 3.0 delivers cinematic results with efficiency, flexibility, and creative control.

Happy Horse is an AI video generation and editing platform designed to help creators transform prompts, images, references, and first-frame ideas into cinematic video content. The platform gives users multiple ways to begin a project, including text-based generation, reference-driven generation, first-frame input, and video editing. Creators can generate videos from imaginative concepts, then modify details to refine the final result. Happy Horse is built for visual experimentation, storytelling, and AI cinema, making it useful for artists who want to explore ideas quickly without traditional production barriers. Its creative environment includes featured projects, community videos, short AI films, and showcase content from different creators. The platform also highlights AI cinema events, encouraging users to submit and celebrate AI-made cinematic work. Users can sign in to receive free credits and take advantage of special offers for additional generation access. Happy Horse supports short-form video experimentation, concept development, visual storytelling, and creative exploration. The platform’s tools help users turn sparks of imagination into videos that can be shared, refined, or developed into larger creative projects. Its combination of generation, reference input, first-frame control, editing, and community inspiration makes it a practical workspace for AI video creators. Happy Horse helps filmmakers, designers, artists, and everyday creators bring visual ideas to life with speed, flexibility, and expressive control.

The Nano Banana 2 Lite is Google's quickest Gemini Image model in the Nano Banana lineup, designed for outstanding speed, scalability, and throughput. Known as the Gemini 3.1 Flash Lite Image, it is specifically tailored for rapid ideation and fast-paced developer workflows that emphasize quickness, swift iterations, and streamlined production methods. This model is recommended as an upgrade over its predecessor, the original Nano Banana, enabling developers to gain immediate benefits in crucial performance areas while improving their image generation and editing processes via Google AI Studio, Gemini API, and the Gemini Enterprise Agent Platform. Optimized for near-real-time, high-volume applications where ultra-low latency is critical, the Nano Banana 2 Lite can produce text-to-image outputs in just seconds, making it perfect for interactive prototyping, visual drafting, creative experimentation, and large-scale image generation. As the need for speed and efficiency in image processing continues to escalate, this model emerges as a vital resource for developers who aim to elevate their creative capacities and push the boundaries of their projects even further. Its innovative features position it as a pivotal element in modern development environments.

OpenAI's Images 2.5 represents a state-of-the-art advancement in image modeling, offering remarkable enhancements in detail, accuracy in editing, faster generation times, and advanced tools for visual creation and refinement. This model achieves a more realistic portrayal of lighting and richer textures while maintaining the consistency of subjects in reference images, allowing for greater precision in responding to editing requests across multiple uses. The significant reduction in generation latency, by up to 50% compared to its predecessor, empowers users to quickly iterate on their creative concepts. Images 2.5 is particularly adept at making targeted changes to specific elements while ensuring that the overall subject, composition, background, and surrounding details remain intact. Moreover, during prolonged editing discussions, earlier edits are more likely to be preserved, thus avoiding any potential decline in image quality over time. Additionally, the model demonstrates a heightened ability to comprehend complex visual instructions, real-world contexts, artistic styles, transparent backgrounds, layouts, and intricate compositions, which streamlines the creative process for users. Ultimately, this breakthrough results in a more fluid and engaging experience for those involved in visual editing, further enhancing their creative endeavors. By facilitating faster and more precise edits, OpenAI’s Images 2.5 revolutionizes how users approach their visual projects.

ChatGPT Images 2.6 is a generative artificial intelligence model developed by OpenAI for creating, editing, and animating digital images through natural language interactions. The model enables users to describe visual concepts in text and generate corresponding images without requiring traditional graphic design or illustration tools. Its image-to-image editing capabilities allow existing photographs, illustrations, and other visual materials to be transformed according to user instructions. Users can refine generated content by requesting adjustments to visual composition, backgrounds, subjects, lighting, colors, and stylistic characteristics through ongoing conversations. ChatGPT Images 2.6 introduces native animated GIF generation, allowing users to create short animations directly from written prompts or uploaded reference photographs. The animation workflow supports adjustable playback speeds, individual frame inspection, and targeted editing of specific frames to improve movement and visual consistency. These capabilities support creative applications such as animated social media content, digital illustrations, visual storytelling, promotional materials, and short looping graphics. The model also introduces faster image generation compared with previous versions, helping users experiment with creative ideas and iterate on visual assets more efficiently. ChatGPT Images 2.6 is integrated into ChatGPT and Codex, with a rollout covering supported web, desktop, and mobile experiences. OpenAI also provides GPT-Image-2.6 Flare, an API model optimized for faster image generation, and GPT-Image-2.6 Sunburst, which emphasizes higher-quality results for detailed creative work. Developers can use these API models to incorporate AI image generation and editing into applications, design workflows, content creation tools, and automated multimedia production systems.

GPT-Image-2.6 Flare is a speed-optimized generative artificial intelligence model developed by OpenAI for creating digital images through natural language instructions. The model belongs to the GPT-Image-2.6 family and is designed to provide responsive image generation for applications requiring rapid creative output. It transforms written prompts into visual content, allowing users to describe subjects, compositions, artistic styles, environments, and other image characteristics. Developers can incorporate the model into creative applications that generate illustrations, promotional graphics, concept artwork, product visuals, and other digital assets. Its focus on generation speed supports interactive workflows where users frequently adjust prompts and experiment with different creative directions. Marketing teams and content creators can use applications powered by Flare to produce visual materials for advertising, social media, websites, and digital communications. The model can also support automated image production systems that generate graphics dynamically from user requests, structured application data, or predefined creative instructions. Software companies can integrate its capabilities into image creation tools, design platforms, ecommerce applications, and AI-powered content management workflows. GPT-Image-2.6 Flare is positioned as the faster alternative to GPT-Image-2.6 Sunburst, which is designed to emphasize higher-quality image generation. Both models were introduced as part of OpenAI's Images 2.6 release, which also brought faster image creation and native animated GIF capabilities to ChatGPT. By focusing on responsive visual generation, Flare provides developers with an option for building image-intensive applications that prioritize speed, usability, and efficient creative iteration.

GPT-Image-2.6 Sunburst is an advanced generative artificial intelligence model developed by OpenAI for high-quality image creation and editing. The model belongs to the GPT-Image-2.6 family and is positioned as the quality-focused alternative to the speed-optimized GPT-Image-2.6 Flare model. It enables users to transform written descriptions into original visual content, including illustrations, realistic images, digital artwork, concept designs, and marketing graphics. Natural language prompting allows creators to specify subjects, environments, visual styles, compositions, lighting conditions, and other characteristics of the desired image. Its image editing capabilities support modifications to existing visual assets through instructions describing the changes users want to make. Reference images can provide visual context for transformations, revisions, and other image-based creative workflows. The model is intended for applications where visual consistency, editing precision, and detailed creative results are more important than maximizing generation speed. Designers and marketing professionals can use applications powered by Sunburst to develop advertising materials, social media graphics, branded imagery, and other digital content. Developers can integrate the model into graphic design platforms, ecommerce applications, creative automation systems, and tools that generate visual assets from user prompts. GPT-Image-2.6 Sunburst was introduced as part of OpenAI's Images 2.6 update, which also expanded image generation capabilities across ChatGPT and Codex. By emphasizing high-quality image generation and editing, the model provides businesses and developers with an option for building sophisticated visual creation applications and professional content production workflows.

Seedance 2.0 is an AI-driven video generation platform designed to deliver cinematic storytelling with minimal technical effort. Developed by ByteDance, it transforms text prompts, images, audio, and video clips into cohesive, high-quality videos. The system leverages multimodal intelligence to align visuals, sound, and motion seamlessly. Character fidelity and scene continuity are preserved across multiple shots, even in complex narratives. Seedance 2.0 allows creators to combine up to twelve reference assets in a single workflow. The platform automatically determines camera angles, movement, and pacing based on creative intent. This removes the need for manual editing or animation expertise. Output quality supports full HD and higher resolutions, making it suitable for professional distribution. The model has gone viral for its ability to generate animated and cinematic scenes directly from prompts. It opens new creative opportunities for content creation at scale. However, features such as voice synthesis raise important ethical and privacy considerations. Seedance 2.0 represents a major step forward in AI-powered video production.

ChatGPT Images 2.0 is OpenAI’s latest AI image generation model, designed to create highly realistic and structured visuals from text and other inputs. It replaces earlier models with a reasoning-driven architecture that analyzes prompts before generating images. This allows the system to produce more accurate compositions, better layouts, and improved consistency across outputs. One of its major advancements is near-perfect text rendering, enabling clear and readable text in multiple languages within images. The model supports generating multiple coherent images from a single prompt, maintaining continuity across scenes and characters. It can produce visuals at higher resolutions and handle a wide range of aspect ratios for different use cases. ChatGPT Images 2.0 is capable of generating complex outputs such as infographics, storyboards, marketing assets, and UI designs. Its ability to interpret context and follow detailed instructions makes it more reliable than previous image generation tools. The system also integrates with ChatGPT workflows, allowing users to combine text, images, and other media seamlessly. It is designed to be a practical tool for professionals, not just an experimental art generator. The model can even process uploaded content and transform it into visual outputs. Its improvements in realism and detail make generated images appear closer to real-world visuals. By combining reasoning, multilingual support, and high-quality rendering, ChatGPT Images 2.0 is redefining how AI is used for visual content creation.

Kling 4.0 is an AI video generation model built to provide greater control over visual realism, motion, sound, references, editing, and narrative structure. It supports text-to-video and image-to-video creation as well as first and last frames, multi-keyframes, Omni Reference, and multimodal video editing. A single generation can run from 3 to 30 seconds, enabling longer continuous shots and more complete sequences than the previous Kling generation. Creators can provide up to 10 keyframe images to define important visual moments, character states, scene transitions, and story beats throughout a video. Omni Reference supports combinations of images, videos, voice references, and subjects, with as many as 15 reference assets available within one generation. These references can guide character consistency, product appearance, visual style, composition, movement, camera direction, narrative pacing, and other elements of the resulting footage. Kling 4.0 supports output at 720p, 1080p, and 4K, while 10-bit HDR for 1080p and 4K is planned to provide greater dynamic range for professional production workflows. The model also generates two-channel stereo audio and provides improved lip synchronization, multilingual speech, accents, dialects, and visual text generation across multiple languages. Its video editing capabilities allow targeted modifications to characters, expressions, movements, backgrounds, camera positions, camera movements, and overall visual styles while attempting to keep unaffected portions of the scene stable. Kling 4.0 accepts prompts of up to 8,000 tokens and is designed to interpret both simple instructions and detailed creative direction involving actions, cinematography, audio, and storytelling. Kling AI is positioning the model for applications including filmmaking, short-form video, animation, advertising, product promotion, music videos, game trailers, social content, and other professional or personal video production workflows.