Alternatives to HunyuanCustom

Tencent Hunyuan represents a comprehensive family of multimodal AI models crafted by Tencent, encompassing a range of modalities including text, images, video, and 3D data, all aimed at facilitating general-purpose AI applications such as content creation, visual reasoning, and automating business processes. This model family features various iterations tailored for tasks like natural language interpretation, multimodal comprehension that combines vision and language (such as understanding images and videos), generating images from text, creating videos, and producing 3D content. The Hunyuan models utilize a mixture-of-experts framework alongside innovative strategies, including hybrid "mamba-transformer" architectures, to excel in tasks requiring reasoning, long-context comprehension, cross-modal interactions, and efficient inference capabilities. A notable example is the Hunyuan-Vision-1.5 vision-language model, which facilitates "thinking-on-image," allowing for intricate multimodal understanding and reasoning across images, video segments, diagrams, or spatial information. This robust architecture positions Hunyuan as a versatile tool in the rapidly evolving field of AI, capable of addressing a diverse array of challenges.

HunyuanVideo-Avatar allows for the transformation of any avatar images into high-dynamic, emotion-responsive videos by utilizing straightforward audio inputs. This innovative model is based on a multimodal diffusion transformer (MM-DiT) architecture, enabling the creation of lively, emotion-controllable dialogue videos featuring multiple characters. It can process various styles of avatars, including photorealistic, cartoonish, 3D-rendered, and anthropomorphic designs, accommodating different sizes from close-up portraits to full-body representations. Additionally, it includes a character image injection module that maintains character consistency while facilitating dynamic movements. An Audio Emotion Module (AEM) extracts emotional nuances from a source image, allowing for precise emotional control within the produced video content. Moreover, the Face-Aware Audio Adapter (FAA) isolates audio effects to distinct facial regions through latent-level masking, which supports independent audio-driven animations in scenarios involving multiple characters, enhancing the overall experience of storytelling through animated avatars. This comprehensive approach ensures that creators can craft richly animated narratives that resonate emotionally with audiences.

VideoPoet is an innovative modeling technique that transforms any autoregressive language model or large language model (LLM) into an effective video generator. It comprises several straightforward components. An autoregressive language model is trained across multiple modalities—video, image, audio, and text—to predict the subsequent video or audio token in a sequence. The training framework for the LLM incorporates a range of multimodal generative learning objectives, such as text-to-video, text-to-image, image-to-video, video frame continuation, inpainting and outpainting of videos, video stylization, and video-to-audio conversion. Additionally, these tasks can be combined to enhance zero-shot capabilities. This straightforward approach demonstrates that language models are capable of generating and editing videos with impressive temporal coherence, showcasing the potential for advanced multimedia applications. As a result, VideoPoet opens up exciting possibilities for creative expression and automated content creation.

Qwen3-VL represents the latest addition to Alibaba Cloud's Qwen model lineup, integrating sophisticated text processing with exceptional visual and video analysis capabilities into a cohesive multimodal framework. This model accommodates diverse input types, including text, images, and videos, and it is adept at managing lengthy and intertwined contexts, supporting up to 256 K tokens with potential for further expansion. With significant enhancements in spatial reasoning, visual understanding, and multimodal reasoning, Qwen3-VL's architecture features several groundbreaking innovations like Interleaved-MRoPE for reliable spatio-temporal positional encoding, DeepStack to utilize multi-level features from its Vision Transformer backbone for improved image-text correlation, and text–timestamp alignment for accurate reasoning of video content and time-related events. These advancements empower Qwen3-VL to analyze intricate scenes, track fluid video narratives, and interpret visual compositions with a high degree of sophistication. The model's capabilities mark a notable leap forward in the field of multimodal AI applications, showcasing its potential for a wide array of practical uses.

Qwen3-Omni is a comprehensive multilingual omni-modal foundation model designed to handle text, images, audio, and video, providing real-time streaming responses in both textual and natural spoken formats. Utilizing a unique Thinker-Talker architecture along with a Mixture-of-Experts (MoE) framework, it employs early text-centric pretraining and mixed multimodal training, ensuring high-quality performance across all formats without compromising on text or image fidelity. This model is capable of supporting 119 different text languages, 19 languages for speech input, and 10 languages for speech output. Demonstrating exceptional capabilities, it achieves state-of-the-art performance across 36 benchmarks related to audio and audio-visual tasks, securing open-source SOTA on 32 benchmarks and overall SOTA on 22, thereby rivaling or equaling prominent closed-source models like Gemini-2.5 Pro and GPT-4o. To enhance efficiency and reduce latency in audio and video streaming, the Talker component leverages a multi-codebook strategy to predict discrete speech codecs, effectively replacing more cumbersome diffusion methods. Additionally, this innovative model stands out for its versatility and adaptability across a wide array of applications.

Seaweed, an advanced AI model for video generation created by ByteDance, employs a diffusion transformer framework that boasts around 7 billion parameters and has been trained using computing power equivalent to 1,000 H100 GPUs. This model is designed to grasp world representations from extensive multi-modal datasets, which encompass video, image, and text formats, allowing it to produce videos in a variety of resolutions, aspect ratios, and lengths based solely on textual prompts. Seaweed stands out for its ability to generate realistic human characters that can exhibit a range of actions, gestures, and emotions, alongside a diverse array of meticulously detailed landscapes featuring dynamic compositions. Moreover, the model provides users with enhanced control options, enabling them to generate videos from initial images that help maintain consistent motion and aesthetic throughout the footage. It is also capable of conditioning on both the opening and closing frames to facilitate smooth transition videos, and can be fine-tuned to create content based on specific reference images, thus broadening its applicability and versatility in video production. As a result, Seaweed represents a significant leap forward in the intersection of AI and creative video generation.

Marengo is an advanced multimodal model designed to convert video, audio, images, and text into cohesive embeddings, facilitating versatile “any-to-any” capabilities for searching, retrieving, classifying, and analyzing extensive video and multimedia collections. By harmonizing visual frames that capture both spatial and temporal elements with audio components—such as speech, background sounds, and music—and incorporating textual elements like subtitles and metadata, Marengo crafts a comprehensive, multidimensional depiction of each media asset. With its sophisticated embedding framework, Marengo is equipped to handle a variety of demanding tasks, including diverse types of searches (such as text-to-video and video-to-audio), semantic content exploration, anomaly detection, hybrid searching, clustering, and recommendations based on similarity. Recent iterations have enhanced the model with multi-vector embeddings that distinguish between appearance, motion, and audio/text characteristics, leading to marked improvements in both accuracy and contextual understanding, particularly for intricate or lengthy content. This evolution not only enriches the user experience but also broadens the potential applications of the model in various multimedia industries.

Gen-2: Advancing the Frontier of Generative AI. This innovative multi-modal AI platform is capable of creating original videos from text, images, or existing video segments. It can accurately and consistently produce new video content by either adapting the composition and style of a source image or text prompt to the framework of an existing video (Video to Video), or by solely using textual descriptions (Text to Video). This process allows for the creation of new visual narratives without the need for actual filming. User studies indicate that Gen-2's outputs are favored over traditional techniques for both image-to-image and video-to-video transformation, showcasing its superiority in the field. Furthermore, its ability to seamlessly blend creativity and technology marks a significant leap forward in generative AI capabilities.

Hailuo 2.3 represents a state-of-the-art AI video creation model accessible via the Hailuo AI platform, enabling users to effortlessly produce short videos from text descriptions or still images, featuring seamless motion, authentic expressions, and a polished cinematic finish. This model facilitates multi-modal workflows, allowing users to either narrate a scene in straightforward language or upload a reference image, subsequently generating vibrant and fluid video content within seconds. It adeptly handles intricate movements like dynamic dance routines and realistic facial micro-expressions, showcasing enhanced visual consistency compared to previous iterations. Furthermore, Hailuo 2.3 improves stylistic reliability for both anime and artistic visuals, elevating realism in movement and facial expressions while ensuring consistent lighting and motion throughout each clip. A Fast mode variant is also available, designed for quicker processing and reduced costs without compromising on quality, making it particularly well-suited for addressing typical challenges encountered in ecommerce and marketing materials. This advancement opens up new possibilities for creative expression and efficiency in video production.

Wan2.5-Preview arrives with a groundbreaking multimodal foundation that unifies understanding and generation across text, imagery, audio, and video. Its native multimodal design, trained jointly across diverse data sources, enables tighter modal alignment, smoother instruction execution, and highly coherent audio-visual output. Through reinforcement learning from human feedback, it continually adapts to aesthetic preferences, resulting in more natural visuals and fluid motion dynamics. Wan2.5 supports cinematic 1080p video generation with synchronized audio, including multi-speaker content, layered sound effects, and dynamic compositions. Creators can control outputs using text prompts, reference images, or audio cues, unlocking a new range of storytelling and production workflows. For still imagery, the model achieves photorealism, artistic versatility, and strong typography, plus professional-level chart and design rendering. Its editing tools allow users to perform conversational adjustments, merge concepts, recolor products, modify materials, and refine details at pixel precision. This preview marks a major leap toward fully integrated multimodal creativity powered by AI.

HunyuanVideo is a cutting-edge video generation model powered by AI, created by Tencent, that expertly merges virtual and real components, unlocking endless creative opportunities. This innovative tool produces videos of cinematic quality, showcasing smooth movements and accurate expressions while transitioning effortlessly between lifelike and virtual aesthetics. By surpassing the limitations of brief dynamic visuals, it offers complete, fluid actions alongside comprehensive semantic content. As a result, this technology is exceptionally suited for use in various sectors, including advertising, film production, and other commercial ventures, where high-quality video content is essential. Its versatility also opens doors for new storytelling methods and enhances viewer engagement.

HunyuanVision, an innovative vision-language model created by Tencent's Hunyuan team, employs a mamba-transformer hybrid architecture that excels in performance and offers efficient inference for multimodal reasoning challenges. The latest iteration, Hunyuan-Vision-1.5, focuses on the concept of “thinking on images,” enabling it to not only comprehend the interplay of visual and linguistic content but also engage in advanced reasoning that includes tasks like cropping, zooming, pointing, box drawing, or annotating images for enhanced understanding. This model is versatile, supporting various vision tasks such as image and video recognition, OCR, and diagram interpretation, in addition to facilitating visual reasoning and 3D spatial awareness, all within a cohesive multilingual framework. Designed for compatibility across different languages and tasks, HunyuanVision aims to be open-sourced, providing access to checkpoints, a technical report, and inference support to foster community engagement and experimentation. Ultimately, this initiative encourages researchers and developers to explore and leverage the model's capabilities in diverse applications.

OmniHuman-1 is an innovative AI system created by ByteDance that transforms a single image along with motion cues, such as audio or video, into realistic human videos. This advanced platform employs multimodal motion conditioning to craft lifelike avatars that exhibit accurate gestures, synchronized lip movements, and facial expressions that correspond with spoken words or music. It has the flexibility to handle various input types, including portraits, half-body, and full-body images, and can generate high-quality videos even when starting with minimal audio signals. The capabilities of OmniHuman-1 go beyond just human representation; it can animate cartoons, animals, and inanimate objects, making it ideal for a broad spectrum of creative uses, including virtual influencers, educational content, and entertainment. This groundbreaking tool provides an exceptional method for animating static images, yielding realistic outputs across diverse video formats and aspect ratios, thereby opening new avenues for creative expression. Its ability to seamlessly integrate various forms of media makes it a valuable asset for content creators looking to engage audiences in fresh and dynamic ways.

HappyHorse 1.1 is a newly upgraded AI video model built to support higher-quality professional video generation. Since the release of HappyHorse 1.0, the model has been used across short drama production, ecommerce advertising, brand marketing, CG, and other content workflows. HappyHorse 1.1 improves motion modeling and temporal consistency so characters and objects move more naturally through complex action scenes. The model also strengthens subject consistency and multi-reference fusion, making it easier to preserve character identity, product details, brand assets, environments, storyboards, and multi-panel references. Its improved instruction following helps the model better understand creative intent, character relationships, long-context prompts, and multi-scene narrative planning. HappyHorse 1.1 upgrades visual quality with more detailed character rendering, more natural skin texture, better close-up expressiveness, and stronger cinematic camera language. It also improves audio expression by making dialogue, pacing, pauses, tone, ambient sound, background music, and sound effects better match the scene. Developers and enterprise customers can access HappyHorse 1.1 through API support for T2V, I2V, R2V, multi-image references, flexible aspect ratios, and 720p or 1080p output. HappyHorse 1.1 helps creative teams produce smoother, more realistic, better synchronized, and more controllable AI-generated videos.

Seedance 1.5 Pro, an advanced AI model for audio and video generation, has been created by the Seed research team at ByteDance to produce synchronized video and sound seamlessly from text prompts alongside image or visual inputs, which removes the conventional approach of generating visuals before adding audio. This innovative model is designed for joint audio-visual generation, achieving precise lip-sync and motion alignment while offering support for multilingual audio and spatial sound effects that enhance the storytelling experience. Furthermore, it ensures visual consistency and maintains cinematic motion throughout multi-shot sequences, accommodating camera movements and narrative continuity. The system can generate short clips, typically ranging from 4 to 12 seconds, in resolutions up to 1080p and features expressive motion, stable aesthetics, and options for controlling the first and last frames. It caters to both text-to-video and image-to-video workflows, enabling creators to animate still images or construct complete cinematic sequences that flow coherently, thus expanding creative possibilities in audiovisual production. Ultimately, Seedance 1.5 Pro stands as a transformative tool for content creators aiming to elevate their storytelling capabilities.

LTX-2.3 represents a cutting-edge AI video generation model that transforms text prompts, images, or various media inputs into high-quality videos, all while ensuring precise control over motion, structure, and the synchronization of audio and visuals. This model is a key component of the LTX series of multimodal generative tools aimed at developers and production teams seeking scalable solutions for programmatic video creation and editing. Enhancements over previous LTX versions include improved detail rendering, greater motion consistency, superior prompt comprehension, and enhanced audio quality throughout the video creation process. One of its standout features is a newly designed latent representation, utilizing an upgraded VAE trained on more refined datasets, which significantly enhances the retention of intricate details such as fine textures, edges, and small visual elements like hair, text, and complex surfaces across multiple frames. This evolution in video generation technology marks a significant leap forward for creators and professionals in the multimedia domain.

Wan 2.6 is a state-of-the-art video generation model developed by Alibaba for high-fidelity multimodal content creation. It enables users to generate short videos directly from text prompts, images, or existing video inputs. The model produces clips up to 15 seconds long while preserving visual coherence and storytelling quality. Built-in audio and visual synchronization ensures that speech, music, and sound effects match the generated visuals seamlessly. Wan 2.6 delivers fluid motion, realistic character animation, and smooth camera transitions. Advanced lip-sync capabilities enhance realism in dialogue-driven scenes. The model supports multiple resolutions, making it suitable for professional and social media use. Users can animate still images into consistent video sequences without losing character identity. Flexible prompt handling supports multiple languages natively. Wan 2.6 streamlines short-form video production with speed and precision.

Ray2 represents a cutting-edge video generation model that excels at producing lifelike visuals combined with fluid, coherent motion. Its proficiency in interpreting text prompts is impressive, and it can also process images and videos as inputs. This advanced model has been developed using Luma’s innovative multi-modal architecture, which has been enhanced to provide ten times the computational power of its predecessor, Ray1. With Ray2, we are witnessing the dawn of a new era in video generation technology, characterized by rapid, coherent movement, exquisite detail, and logical narrative progression. These enhancements significantly boost the viability of the generated content, resulting in videos that are far more suitable for production purposes. Currently, Ray2 offers text-to-video generation capabilities, with plans to introduce image-to-video, video-to-video, and editing features in the near future. The model elevates the quality of motion fidelity to unprecedented heights, delivering smooth, cinematic experiences that are truly awe-inspiring. Transform your creative ideas into stunning visual narratives, and let Ray2 help you create mesmerizing scenes with accurate camera movements that bring your story to life. In this way, Ray2 empowers users to express their artistic vision like never before.

CogVideoX-3 is an advanced video generation model that enhances frame creation, resulting in improved image clarity and stability. It excels in scenarios involving fast-moving subjects, follows instructions more accurately, and offers highly realistic video simulations. The model accommodates various input types including images, text, and start-and-end-frame sequences, producing video outputs, which broadens its application in text-to-video, image-to-video, and transitional video processes. This versatility makes CogVideoX-3 particularly valuable for advertising and marketing, enabling users to input product visuals or marketing copy to swiftly generate engaging ads in diverse styles, while also supporting realistic lighting and seamless scene transitions. Additionally, it facilitates the production of short videos by transforming single-frame images or written scripts into fluid, naturally animated clips, available in both realistic and 3D formats. For tourism marketing, users can simply upload scenic photographs along with promotional text to create captivating short videos that enhance the appeal of travel destinations, effectively drawing in potential visitors. Ultimately, CogVideoX-3 empowers creators across various industries to produce high-quality video content with ease.

BytePlus Seedance offers official access to Seedance 2.5, an advanced AI video generation model that enables the production of professional-grade videos from various inputs, including text, images, audio, and video. This innovative model employs a unified multimodal architecture for audio-video joint generation, which equips creators with extensive reference and editing tools for precise video crafting. It facilitates multiple workflows, such as transforming text into video, converting images into moving visuals, and engaging in multimodal generation, allowing users to turn concepts, images, reference clips, and sound cues into cinematic masterpieces. Designed for an immersive audiovisual experience, Seedance 2.5 boasts remarkable motion stability and integrated audio-video generation, ensuring the creation of ultra-realistic scenes with fluid movements and perfectly synchronized sound. With a focus on director-level control, the model allows the use of images, audio, and video as references, empowering creators to direct aspects like performance, lighting, shadows, camera movements, scene direction, and overall visual style. This flexibility makes Seedance 2.5 a powerful tool for innovative storytellers looking to elevate their craft.

The Kling 3.0 Omni model represents an innovative generative video platform that crafts creative videos from text inputs, images, or other reference materials by utilizing cutting-edge multimodal AI technology. This system enables the production of seamless video clips with duration options that span from about 3 to 15 seconds, perfect for creating brief cinematic sequences that align closely with user prompts. Additionally, it accommodates both prompt-driven video creation and workflows based on visual references, allowing users to input images or other visual cues to influence the scene's subject, style, or composition. By enhancing prompt fidelity and maintaining subject consistency, the model ensures that characters, objects, and environments exhibit stability throughout the duration of the video while also delivering realistic motion and visual coherence. Moreover, the Omni model significantly boosts reference-based generation, ensuring that characters or elements introduced via images retain their recognizability across multiple frames, thereby enriching the overall viewing experience. This capability makes it an invaluable tool for creators seeking to produce visually engaging content with ease and precision.

WaveSpeedAI stands out as a powerful generative media platform engineered to significantly enhance the speed of creating images, videos, and audio by leveraging advanced multimodal models paired with an exceptionally quick inference engine. It accommodates a diverse range of creative processes, including transforming text into video, converting images into video, generating images from text, producing voice content, and developing 3D assets, all through a cohesive API built for scalability and rapid performance. The platform integrates leading foundation models such as WAN 2.1/2.2, Seedream, FLUX, and HunyuanVideo, granting users seamless access to an extensive library of models. With its remarkable generation speeds, real-time processing capabilities, and enterprise-level reliability, users enjoy consistently high-quality outcomes. WaveSpeedAI focuses on delivering a “fast, vast, efficient” experience, ensuring quick production of creative assets, access to a comprehensive selection of cutting-edge models, and economical execution that maintains exceptional quality. Additionally, this platform is tailored to meet the demands of modern creators, making it an indispensable tool for anyone looking to elevate their media production capabilities.

HunyuanWorld-1.0 is an open-source AI framework and generative model created by Tencent Hunyuan, designed to generate immersive, interactive 3D environments from text inputs or images by merging the advantages of both 2D and 3D generation methods into a single cohesive process. Central to the framework is a semantically layered 3D mesh representation that utilizes 360° panoramic world proxies to break down and rebuild scenes with geometric fidelity and semantic understanding, allowing for the generation of varied and coherent spaces that users can navigate and engage with. In contrast to conventional 3D generation techniques that often face challenges related to limited diversity or ineffective data representations, HunyuanWorld-1.0 adeptly combines panoramic proxy creation, hierarchical 3D reconstruction, and semantic layering to achieve a synthesis of high visual quality and structural soundness, while also providing exportable meshes that fit seamlessly into standard graphics workflows. This innovative approach not only enhances the realism of generated environments but also opens new possibilities for creative applications in various industries.

Ming-Flash Omni 2.0, developed by Ant Group, represents a comprehensive large language model that operates on a cohesive multimodal framework, emphasizing a philosophy of “modal unity + task unity.” This model, as a part of the Ming series, is engineered to facilitate an integrated understanding and generation of content across various modalities, including text, images, audio, and video, thus eliminating the need for multiple specialized models to perform distinct tasks such as seeing, hearing, speaking, and drawing. Progressing from its predecessors, Ming-Light Omni and Ming-Flash Omni Preview, this iteration advances from validating a unified architecture and scaling to hundreds of billions of parameters to implementing a Data Scaling approach that achieves state-of-the-art performance in open-source environments across numerous benchmarks. Notably, the model encompasses four essential capability modules: image-text comprehension, video interpretation, speech generation, and image creation or manipulation. To enhance image-text understanding, Ming employs structured knowledge graphs that contribute to a more nuanced visual perception. This innovative approach not only broadens the model's applicability but also sets a new standard in the field of artificial intelligence.

Kling O1 serves as a generative AI platform that converts text, images, and videos into high-quality video content, effectively merging video generation with editing capabilities into a cohesive workflow. It accommodates various input types, including text-to-video, image-to-video, and video editing, and features an array of models, prominently the “Video O1 / Kling O1,” which empowers users to create, remix, or modify clips utilizing natural language prompts. The advanced model facilitates actions such as object removal throughout an entire clip without the need for manual masking or painstaking frame-by-frame adjustments, alongside restyling and the effortless amalgamation of different media forms (text, image, and video) for versatile creative projects. Kling AI prioritizes smooth motion, authentic lighting, cinematic-quality visuals, and precise adherence to user prompts, ensuring that actions, camera movements, and scene transitions closely align with user specifications. This combination of features allows creators to explore new dimensions of storytelling and visual expression, making the platform a valuable tool for both professionals and hobbyists in the digital content landscape.

The NVIDIA Nemotron 3 Nano Omni represents a groundbreaking open foundation model that integrates various modes of perception and reasoning—including text, images, audio, video, and documents—into a single streamlined architecture. By eliminating the necessity for distinct models tailored to each modality, it effectively minimizes inference delays, simplifies orchestration, and lowers costs while ensuring a cohesive cross-modal context. This innovative model is specifically engineered for agentic AI systems, functioning as a perception and context sub-agent that empowers larger AI entities to perceive and interpret their surroundings in real-time across various formats such as screens, recordings, and both structured and unstructured data. Its capabilities extend to complex multimodal reasoning tasks, encompassing document comprehension, speech recognition, extensive audio-video analysis, and intricate computer workflows, thus allowing agents to navigate dynamic interfaces and multifaceted environments with ease. With a hybrid architecture that is finely tuned for handling long contexts and high throughput, the Nemotron 3 Nano Omni is adept at managing sizable inputs, including multi-page documents, making it a versatile tool in the realm of AI development. Not only does it unify modalities, but it also enhances the overall efficiency of intelligent systems in processing and understanding diverse data types.

Seedance 2.0 is a next-generation AI video creation model developed by ByteDance to simplify high-quality video production. It allows users to generate complete videos using text, images, audio, and existing clips as creative inputs. The platform excels at maintaining visual coherence, ensuring characters, styles, and scenes remain consistent across shots. Advanced motion synthesis enables smooth transitions and realistic camera movement throughout each video. Users can reference multiple assets at once, combining visuals and sound to shape the final output. Seedance 2.0 removes the need for traditional editing tools by handling pacing and shot composition automatically. Videos are produced in professional-grade resolutions suitable for commercial use. The model has gained attention for producing complex animated sequences, including anime-style visuals. It empowers individual creators and small teams to achieve studio-like results. At the same time, it introduces new conversations around responsible AI use and content authenticity.

Veo 3.1 Fast represents a major leap forward in generative video technology, combining the creative intelligence of Veo 3.1 with faster generation times and expanded control. Available through the Gemini API, the model turns written prompts and still images into cinematic videos with synchronized sound and expressive storytelling. Developers can guide scene generation using up to three reference images, extend video length continuously with “Scene Extension,” and even create dynamic transitions between first and last frames. Its enhanced AI engine maintains character and visual consistency across sequences while improving adherence to user intent and narrative tone. Veo 3.1 Fast’s audio generation adds depth with natural voices and realistic soundscapes, enabling richer, more immersive outputs. Integration with Google AI Studio and Gemini Enterprise Agent Platform makes it simple to build, test, and deploy creative applications. Leading creative teams, such as Promise Studios and Latitude, are already using Veo 3.1 Fast for generative filmmaking and interactive storytelling. Offering the same price as Veo 3.0 but vastly improved capability, it sets a new benchmark for AI-driven video production.

Veo 3.1 expands upon the features of its predecessor, allowing for the creation of longer and more adaptable AI-generated videos. This upgraded version empowers users to produce multi-shot videos based on various prompts, generate sequences using three reference images, and incorporate frames in video projects that smoothly transition between a starting and ending image, all while maintaining synchronized, native audio. A notable addition is the scene extension capability, which permits the lengthening of the last second of a clip by up to an entire minute of newly generated visuals and sound. Furthermore, Veo 3.1 includes editing tools for adjusting lighting and shadow effects, enhancing realism and consistency throughout the scenes, and features advanced object removal techniques that intelligently reconstruct backgrounds to eliminate unwanted elements from the footage. These improvements render Veo 3.1 more precise in following prompts, present a more cinematic experience, and provide a broader scope compared to models designed for shorter clips. Additionally, developers can easily utilize Veo 3.1 through the Gemini API or via the Flow tool, which is specifically aimed at enhancing professional video production workflows. This new version not only refines the creative process but also opens up new avenues for innovation in video content creation.

Gen-3 Alpha marks the inaugural release in a new line of models developed by Runway, leveraging an advanced infrastructure designed for extensive multimodal training. This model represents a significant leap forward in terms of fidelity, consistency, and motion capabilities compared to Gen-2, paving the way for the creation of General World Models. By being trained on both videos and images, Gen-3 Alpha will enhance Runway's various tools, including Text to Video, Image to Video, and Text to Image, while also supporting existing functionalities like Motion Brush, Advanced Camera Controls, and Director Mode. Furthermore, it will introduce new features that allow for more precise manipulation of structure, style, and motion, offering users even greater creative flexibility.

MiniMax is an AI platform that provides multimodal foundation models, developer tools, and intelligent agent solutions designed to support coding, automation, content generation, and enterprise AI applications. The company’s flagship model, MiniMax M3, delivers advanced coding performance, long-context processing capabilities of up to one million tokens, and native multimodal functionality that enables seamless understanding and generation of text, audio, images, video, and music. MiniMax Code serves as an AI-powered coding environment that allows users to build agent teams, automate repetitive development tasks, create custom skills, and manage workflows through a unified conversational interface. In addition to coding solutions, the platform offers video generation through Hailuo AI, speech and music generation models, conversational AI products, and developer APIs for integrating AI into custom applications. The platform is designed to support both individual users and enterprise teams seeking scalable AI tools for software development, business automation, creative production, and research. By combining frontier AI models with practical productivity applications, MiniMax enables organizations to streamline operations, enhance innovation, and build intelligent systems more efficiently.

Tencent HY is a versatile and comprehensive family of large models developed in-house by Tencent, designed to deliver AI solutions tailored for enterprise needs across various domains such as content creation, business automation, and real-world agent functionalities. It encompasses multiple modalities, including language, imagery, 3D modeling, and translation, seamlessly integrating Tencent’s proprietary algorithms with advanced natural language processing and computer vision technologies to enable superior image generation, 3D content creation, and intelligent applications. Via Tencent Hunyuan AI Studio, users can engage with the model through intuitive human-computer dialogue, which allows the system to comprehend commands, perform tasks, assist users in information retrieval, generate content, and discover the model's extensive capabilities in a user-friendly environment. Additionally, Tencent HY facilitates API integration and customizable parameter configurations, enhancing accessibility and usability for developers, product teams, and enterprise-focused applications. This adaptability ensures that a wide range of users can leverage the power of Tencent HY in their projects, driving innovation and efficiency across industries.

Kling 2.6 is a next-generation AI video model built to merge sound and visuals into a single, seamless creative process. It eliminates the need for separate voiceovers, sound effects, and audio mixing by generating everything at once. Users can create complete videos from either text prompts or images with synchronized audio output. Kling 2.6 produces natural speech, ambient soundscapes, and action-based sound effects that match visual motion and pacing. The Native Audio system ensures emotional consistency between dialogue, background audio, and scene dynamics. Creators have control over who speaks, how they sound, and the overall mood of the video. The model supports narration, dialogue, music, and mixed sound effects. Kling 2.6 simplifies professional video creation for small teams and solo creators. Its intuitive workflow reduces technical complexity while maintaining creative flexibility. The result is faster production of immersive, shareable video content.

Nova 2 Omni is an innovative model that seamlessly integrates multimodal reasoning and generation, allowing it to comprehend and generate diverse types of content, including text, images, video, and audio. Its capability to process exceptionally large inputs, which can encompass hundreds of thousands of words or several hours of audiovisual material, enables it to maintain a coherent analysis across various formats. As a result, it can simultaneously analyze comprehensive product catalogs, extensive documents, customer reviews, and entire video libraries, providing teams with a singular system that eliminates the necessity for multiple specialized models. By managing mixed media within a unified workflow, Nova 2 Omni paves the way for new opportunities in both creative and operational automation. For instance, a marketing team can input product specifications, brand standards, reference visuals, and video content to effortlessly generate an entire campaign that includes messaging, social media content, and visuals, all in one streamlined process. This efficiency not only enhances productivity but also fosters innovation in how teams approach their marketing strategies.

Wan2.2 Animate is a dedicated component of the Wan video generation suite, which focuses on producing high-quality character animations and facilitating character swaps in videos. This module empowers users to convert still images into lively videos or change subjects in pre-existing clips while ensuring that realism and motion continuity are upheld. It operates by utilizing two main inputs: a reference image that illustrates the character's look and a reference video that conveys the necessary motion, expressions, and context of the scene. By combining these elements, it can effectively bring a static character to life by mirroring the body movements, gestures, and facial expressions from the provided video or replace an existing character while keeping the original lighting, camera dynamics, and surrounding environment intact for a fluid transition. The technology employs sophisticated methodologies, including spatially aligned skeleton signals and implicit facial feature extraction, to faithfully capture and reproduce the nuances of movement and expression. Moreover, the module's innovative design allows for a wide range of creative applications in filmmaking and animation, making it a valuable tool for content creators.

SeyftAI is an advanced platform for real-time, multi-modal content moderation that effectively screens harmful and irrelevant materials across various formats, including text, images, and videos, to guarantee compliance while providing customized solutions for different languages and cultural nuances. With a wide-ranging set of tools, SeyftAI assists in maintaining clean and safe digital environments. It can identify and eliminate harmful textual content in numerous languages effortlessly. The API provided by SeyftAI facilitates the smooth integration of its content moderation features into your existing applications and workflows. Additionally, it can autonomously detect and filter out inappropriate or explicit images without the need for human oversight. SeyftAI enables users to customize content moderation workflows according to their unique requirements. Furthermore, users can obtain detailed reports and analytics on their content moderation efforts, enhancing transparency and effectiveness. By utilizing this platform, businesses can ensure that their digital content remains safe and compliant, adapting to the ever-evolving landscape of online interactions.

Veo 3 is Google’s most advanced video generation tool, built to empower filmmakers and creatives with unprecedented realism and control. Offering 4K resolution video output, real-world physics, and native audio generation, it allows creators to bring their visions to life with enhanced realism. The model excels in adhering to complex prompts, ensuring that every scene or action unfolds exactly as envisioned. Veo 3 introduces powerful features such as precise camera controls, consistent character appearance across scenes, and the ability to add sound effects, ambient noise, and dialogue directly into the video. These new capabilities open up new possibilities for both professional filmmakers and enthusiasts, offering full creative control while maintaining a seamless and natural flow throughout the production.

Kling 3.0 is a next-generation AI video creation model designed for producing highly realistic and cinematic video content. It transforms text and image prompts into visually rich scenes with smooth motion and accurate physics. The model excels at maintaining character consistency, ensuring natural expressions and stable identities across frames. Improved understanding of prompts allows for precise control over camera movement, transitions, and scene composition. Kling 3.0 supports higher resolution outputs suitable for professional use cases. Faster rendering capabilities help creators move from idea to finished video more efficiently. The system reduces the technical complexity traditionally associated with video production. It enables creative experimentation without the need for large production teams. Kling 3.0 is well suited for storytelling, advertising, and branded content creation. Overall, it delivers professional-grade results with minimal setup and effort.

Runway Aleph represents a revolutionary advancement in in-context video modeling, transforming the landscape of multi-task visual generation and editing by allowing extensive modifications on any video clip. This model can effortlessly add, delete, or modify objects within a scene, create alternative camera perspectives, and fine-tune style and lighting based on either natural language commands or visual cues. Leveraging advanced deep-learning techniques and trained on a wide range of video data, Aleph functions entirely in context, comprehending both spatial and temporal dynamics to preserve realism throughout the editing process. Users are empowered to implement intricate effects such as inserting objects, swapping backgrounds, adjusting lighting dynamically, and transferring styles without the need for multiple separate applications for each function. The user-friendly interface of this model is seamlessly integrated into Runway's Gen-4 ecosystem, providing an API for developers alongside a visual workspace for creators, making it a versatile tool for both professionals and enthusiasts in video editing. With its innovative capabilities, Aleph is set to revolutionize how creators approach video content transformation.

Runway Gen-4.5 stands as a revolutionary text-to-video AI model by Runway, offering stunningly realistic and cinematic video results with unparalleled precision and control. This innovative model marks a significant leap in AI-driven video production, effectively utilizing pre-training data and advanced post-training methods to redefine the limits of video creation. Gen-4.5 particularly shines in generating dynamic actions that are controllable, ensuring temporal consistency while granting users meticulous oversight over various elements such as camera movement, scene setup, timing, and mood, all achievable through a single prompt. As per independent assessments, it boasts the top ranking on the "Artificial Analysis Text-to-Video" leaderboard, scoring an impressive 1,247 Elo points and surpassing rival models developed by larger laboratories. This capability empowers creators to craft high-quality video content from initial idea to final product, all without reliance on conventional filmmaking tools or specialized knowledge. The ease of use and efficiency of Gen-4.5 further revolutionizes the landscape of video production, making it accessible to a broader audience.

Ray3.14 represents the pinnacle of Luma AI’s generative video technology, engineered to produce high-caliber, ready-for-broadcast video at a native resolution of 1080p, while also enhancing speed, efficiency, and reliability. This model is capable of generating video content up to four times faster than its predecessor and does so at approximately one-third of the cost, ensuring superior alignment with user prompts and enhanced motion consistency throughout frames. It inherently accommodates 1080p resolution in essential processes like text-to-video, image-to-video, and video-to-video, removing the necessity for post-production upscaling, thereby making the outputs immediately viable for broadcast, streaming, and digital platforms. Furthermore, Ray3.14 significantly boosts temporal motion accuracy and visual stability, particularly beneficial for animations and intricate scenes, as it effectively resolves issues such as flickering and drift, thus allowing creative teams to quickly adapt and iterate within tight production schedules. In essence, it builds upon the reasoning-driven video generation capabilities introduced by the earlier Ray3 model, pushing the boundaries of what generative video can achieve. This advancement in technology not only streamlines the creative process but also paves the way for innovative storytelling techniques in the digital landscape.

Wan2.1 represents an innovative open-source collection of sophisticated video foundation models aimed at advancing the frontiers of video creation. This state-of-the-art model showcases its capabilities in a variety of tasks, such as Text-to-Video, Image-to-Video, Video Editing, and Text-to-Image, achieving top-tier performance on numerous benchmarks. Designed for accessibility, Wan2.1 is compatible with consumer-grade GPUs, allowing a wider range of users to utilize its features, and it accommodates multiple languages, including both Chinese and English for text generation. The model's robust video VAE (Variational Autoencoder) guarantees impressive efficiency along with superior preservation of temporal information, making it particularly well-suited for producing high-quality video content. Its versatility enables applications in diverse fields like entertainment, marketing, education, and beyond, showcasing the potential of advanced video technologies.

Azure AI Content Understanding empowers organizations to convert unstructured multimodal data into actionable insights. By extracting valuable information from various input formats including text, audio, images, and video, businesses can unlock essential insights. Employing advanced AI techniques like schema extraction and grounding, it ensures the generation of accurate, high-quality data suitable for further applications. This technology simplifies the integration of diverse data types into a cohesive workflow, resulting in reduced costs and an expedited path to value realization. For instance, businesses and call center operators can leverage insights from call recordings to monitor crucial KPIs, improve product experiences, and respond to customer inquiries more efficiently and accurately. Furthermore, by ingesting a wide array of data types such as documents, images, audio, or video, organizations can utilize various AI models offered in Azure AI to convert raw input into structured outputs that facilitate easier processing and analysis in subsequent applications. Such capabilities ultimately enhance decision-making processes across various sectors.

GLM-4.5V is an evolution of the GLM-4.5-Air model, incorporating a Mixture-of-Experts (MoE) framework that boasts a remarkable total of 106 billion parameters, with 12 billion specifically dedicated to activation. This model stands out by delivering top-tier performance among open-source vision-language models (VLMs) of comparable scale, demonstrating exceptional capabilities across 42 public benchmarks in diverse contexts such as images, videos, documents, and GUI interactions. It offers an extensive array of multimodal functionalities, encompassing image reasoning tasks like scene understanding, spatial recognition, and multi-image analysis, alongside video comprehension tasks that include segmentation and event recognition. Furthermore, it excels in parsing complex charts and lengthy documents, facilitating GUI-agent workflows through tasks like screen reading and desktop automation, while also providing accurate visual grounding by locating objects and generating bounding boxes. Additionally, the introduction of a "Thinking Mode" switch enhances user experience by allowing the selection of either rapid responses or more thoughtful reasoning based on the situation at hand. This innovative feature makes GLM-4.5V not only versatile but also adaptable to various user needs.

Tencent has unveiled the Hunyuan T1, its advanced AI model, which is now accessible to all users via the Tencent Yuanbao platform. This model is particularly adept at grasping various dimensions and potential logical connections, making it ideal for tackling intricate challenges. Users have the opportunity to explore a range of AI models available on the platform, including DeepSeek-R1 and Tencent Hunyuan Turbo. Anticipation is building for the forthcoming official version of the Tencent Hunyuan T1 model, which will introduce external API access and additional services. Designed on the foundation of Tencent's Hunyuan large language model, Yuanbao stands out for its proficiency in Chinese language comprehension, logical reasoning, and effective task performance. It enhances user experience by providing AI-driven search, summaries, and writing tools, allowing for in-depth document analysis as well as engaging prompt-based dialogues. The platform's versatility is expected to attract a wide array of users seeking innovative solutions.