Alternatives to HunyuanCustom

Compare HunyuanCustom alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to HunyuanCustom in 2026. Compare features, ratings, user reviews, pricing, and more from HunyuanCustom competitors and alternatives in order to make an informed decision for your business.

  • 1
    FLUX 3

    FLUX 3

    Black Forest Labs

    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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    MiniMax H3

    MiniMax H3

    MiniMax

    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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    Seedance 2.5

    Seedance 2.5

    ByteDance

    Seedance 2.5 is ByteDance Seed’s new-generation video creation model for long-form storytelling, multimodal reference-based generation, and precise video editing. The model can generate high-quality 30-second audio-video clips in a single pass and supports multi-round extensions for creating longer videos with consistent characters, environments, pacing, and audiovisual style. Seedance 2.5 accepts up to 30 images, 10 video clips, and 10 audio clips as references, giving creators more control over subjects, scenes, motion, camera work, and creative direction. It improves transitions, visual consistency, audio-video synchronization, object textures, skin and eye details, lighting, color, and cinematic realism. The model also supports timestamp-level editing, green screen editing, camera perspective editing, clay render referencing, motion referencing, and reference-based editing.
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    Muse Video
    Muse Video is Meta’s upcoming video generation model from Meta Superintelligence Labs, previewed alongside the launch of Muse Image. The model is built on the same pretraining foundation as Muse Image and is designed to generate high-fidelity videos with native audio support. Muse Video focuses on prompt adherence, visual realism, temporal consistency, and the ability to create short scenes with clear motion, continuity, and audio context. It can generate a wide range of video styles, including cinematic footage, UGC-style ads, animal scenes, product commercials, handheld point-of-view clips, and realistic moments with sound effects, voices, and music. Meta is continuing to improve areas such as audio-video synchronization and physically accurate fast motion before broader release. Coming soon to creators and Meta AI, Muse Video is positioned as a powerful tool for generating dynamic media across Meta’s creative ecosystem.
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    Veo 3.1

    Veo 3.1

    Google

    Veo 3.1 builds on the capabilities of the previous model to enable longer and more versatile AI-generated videos. With this version, users can create multi-shot clips guided by multiple prompts, generate sequences from three reference images, and use frames in video workflows that transition between a start and end image, both with native, synchronized audio. The scene extension feature allows extension of a final second of a clip by up to a full minute of newly generated visuals and sound. Veo 3.1 supports editing of lighting and shadow parameters to improve realism and scene consistency, and offers advanced object removal that reconstructs backgrounds to remove unwanted items from generated footage. These enhancements make Veo 3.1 sharper in prompt-adherence, more cinematic in presentation, and broader in scale compared to shorter-clip models. Developers can access Veo 3.1 via the Gemini API or through the tool Flow, targeting professional video workflows.
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    Veo 3

    Veo 3

    Google

    Veo 3 is Google’s latest state-of-the-art video generation model, designed to bring greater realism and creative control to filmmakers and storytellers. With the ability to generate videos in 4K resolution and enhanced with real-world physics and audio, Veo 3 allows creators to craft high-quality video content with unmatched precision. The model’s improved prompt adherence ensures more accurate and consistent responses to user instructions, making the video creation process more intuitive. It also introduces new features that give creators more control over characters, scenes, and transitions, enabling seamless integration of different elements to create dynamic, engaging videos.
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    HunyuanVideo-Avatar

    HunyuanVideo-Avatar

    Tencent-Hunyuan

    HunyuanVideo‑Avatar supports animating any input avatar images to high‑dynamic, emotion‑controllable videos using simple audio conditions. It is a multimodal diffusion transformer (MM‑DiT)‑based model capable of generating dynamic, emotion‑controllable, multi‑character dialogue videos. It accepts multi‑style avatar inputs, photorealistic, cartoon, 3D‑rendered, anthropomorphic, at arbitrary scales from portrait to full body. Provides a character image injection module that ensures strong character consistency while enabling dynamic motion; an Audio Emotion Module (AEM) that extracts emotional cues from a reference image to enable fine‑grained emotion control over generated video; and a Face‑Aware Audio Adapter (FAA) that isolates audio influence to specific face regions via latent‑level masking, supporting independent audio‑driven animation in multi‑character scenarios.
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    VideoPoet
    VideoPoet is a simple modeling method that can convert any autoregressive language model or large language model (LLM) into a high-quality video generator. It contains a few simple components. An autoregressive language model learns across video, image, audio, and text modalities to autoregressively predict the next video or audio token in the sequence. A mixture of multimodal generative learning objectives are introduced into the LLM training framework, including text-to-video, text-to-image, image-to-video, video frame continuation, video inpainting and outpainting, video stylization, and video-to-audio. Furthermore, such tasks can be composed together for additional zero-shot capabilities. This simple recipe shows that language models can synthesize and edit videos with a high degree of temporal consistency.
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    HunyuanOCR

    HunyuanOCR

    Tencent

    Tencent Hunyuan is a large-scale, multimodal AI model family developed by Tencent that spans text, image, video, and 3D modalities, designed for general-purpose AI tasks like content generation, visual reasoning, and business automation. Its model lineup includes variants optimized for natural language understanding, multimodal vision-language comprehension (e.g., image & video understanding), text-to-image creation, video generation, and 3D content generation. Hunyuan models leverage a mixture-of-experts architecture and other innovations (like hybrid “mamba-transformer” designs) to deliver strong performance on reasoning, long-context understanding, cross-modal tasks, and efficient inference. For example, the vision-language model Hunyuan-Vision-1.5 supports “thinking-on-image”, enabling deep multimodal understanding and reasoning on images, video frames, diagrams, or spatial data.
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    Qwen3-Omni

    Qwen3-Omni

    Alibaba

    Qwen3-Omni is a natively end-to-end multilingual omni-modal foundation model that processes text, images, audio, and video and delivers real-time streaming responses in text and natural speech. It uses a Thinker-Talker architecture with a Mixture-of-Experts (MoE) design, early text-first pretraining, and mixed multimodal training to support strong performance across all modalities without sacrificing text or image quality. The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches.
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    Qwen3-VL

    Qwen3-VL

    Alibaba

    Qwen3-VL is the newest vision-language model in the Qwen family (by Alibaba Cloud), designed to fuse powerful text understanding/generation with advanced visual and video comprehension into one unified multimodal model. It accepts inputs in mixed modalities, text, images, and video, and handles long, interleaved contexts natively (up to 256 K tokens, with extensibility beyond). Qwen3-VL delivers major advances in spatial reasoning, visual perception, and multimodal reasoning; the model architecture incorporates several innovations such as Interleaved-MRoPE (for robust spatio-temporal positional encoding), DeepStack (to leverage multi-level features from its Vision Transformer backbone for refined image-text alignment), and text–timestamp alignment (for precise reasoning over video content and temporal events). These upgrades enable Qwen3-VL to interpret complex scenes, follow dynamic video sequences, read and reason about visual layouts.
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    Seaweed

    Seaweed

    ByteDance

    Seaweed is a foundational AI model for video generation developed by ByteDance. It utilizes a diffusion transformer architecture with approximately 7 billion parameters, trained on a compute equivalent to 1,000 H100 GPUs. Seaweed learns world representations from vast multi-modal data, including video, image, and text, enabling it to create videos of various resolutions, aspect ratios, and durations from text descriptions. It excels at generating lifelike human characters exhibiting diverse actions, gestures, and emotions, as well as a wide variety of landscapes with intricate detail and dynamic composition. Seaweed offers enhanced controls, allowing users to generate videos from images by providing an initial frame to guide consistent motion and style throughout the video. It can also condition on both the first and last frames to create transition videos, and be fine-tuned to generate videos based on reference images.
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    Gen-2

    Gen-2

    Runway

    Gen-2: The Next Step Forward for Generative AI. A multi-modal AI system that can generate novel videos with text, images, or video clips. Realistically and consistently synthesize new videos. Either by applying the composition and style of an image or text prompt to the structure of a source video (Video to Video). Or, using nothing but words (Text to Video). It's like filming something new, without filming anything at all. Based on user studies, results from Gen-2 are preferred over existing methods for image-to-image and video-to-video translation.
    Starting Price: $15 per month
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    Nemotron 3 Nano Omni
    NVIDIA Nemotron 3 Nano Omni is an open, omni-modal foundation model designed to unify perception and reasoning across text, images, audio, video, and documents within a single efficient architecture. It eliminates the need for separate models for each modality, reducing inference latency, orchestration complexity, and cost while maintaining consistent cross-modal context. It is purpose-built for agentic AI systems, acting as a perception and context sub-agent that gives larger AI agents the ability to “see, hear, and read” in real time across screens, recordings, and structured or unstructured data. It supports advanced multimodal reasoning tasks such as document understanding, speech recognition, long audio-video analysis, and computer-use workflows, enabling agents to interpret dynamic interfaces and complex environments. Built with a hybrid architecture optimized for long context and throughput, it can process large inputs like multi-page documents.
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    Marengo

    Marengo

    TwelveLabs

    Marengo is a multimodal video foundation model that transforms video, audio, image, and text inputs into unified embeddings, enabling powerful “any-to-any” search, retrieval, classification, and analysis across vast video and multimedia libraries. It integrates visual frames (with spatial and temporal dynamics), audio (speech, ambient sound, music), and textual content (subtitles, overlays, metadata) to create a rich, multidimensional representation of each media item. With this embedding architecture, Marengo supports robust tasks such as search (text-to-video, image-to-video, video-to-audio, etc.), semantic content discovery, anomaly detection, hybrid search, clustering, and similarity-based recommendation. The latest versions introduce multi-vector embeddings, separating representations for appearance, motion, and audio/text features, which significantly improve precision and context awareness, especially for complex or long-form content.
    Starting Price: $0.042 per minute
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    Wan2.5

    Wan2.5

    Alibaba

    Wan2.5-Preview introduces a next-generation multimodal architecture designed to redefine visual generation across text, images, audio, and video. Its unified framework enables seamless multimodal inputs and outputs, powering deeper alignment through joint training across all media types. With advanced RLHF tuning, the model delivers superior video realism, expressive motion dynamics, and improved adherence to human preferences. Wan2.5 also excels in synchronized audio-video generation, supporting multi-voice output, sound effects, and cinematic-grade visuals. On the image side, it offers exceptional instruction following, creative design capabilities, and pixel-accurate editing for complex transformations. Together, these features make Wan2.5-Preview a breakthrough platform for high-fidelity content creation and multimodal storytelling.
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    Hailuo 2.3

    Hailuo 2.3

    Hailuo AI

    Hailuo 2.3 is a next-generation AI video generator model available through the Hailuo AI platform that lets users create short videos from text prompts or static images with smooth motion, natural expressions, and cinematic polish. It supports multi-modal workflows where you describe a scene in plain language or upload a reference image and then generate vivid, fluid video content in seconds, handling complex motion such as dynamic dance choreography and lifelike facial micro-expressions with improved visual consistency over earlier models. Hailuo 2.3 enhances stylistic stability for anime and artistic video styles, delivers heightened realism in movement and expression, and maintains coherent lighting and motion throughout each generated clip. It offers a Fast mode variant optimized for speed and lower cost while still producing high-quality results, and it is tuned to address common challenges in ecommerce and marketing content.
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    Hunyuan-Vision-1.5
    HunyuanVision is a cutting-edge vision-language model developed by Tencent’s Hunyuan team. It uses a mamba-transformer hybrid architecture to deliver strong performance and efficient inference in multimodal reasoning tasks. The version Hunyuan-Vision-1.5 is designed for “thinking on images,” meaning it not only understands vision+language content, but can perform deeper reasoning that involves manipulating or reflecting on image inputs, such as cropping, zooming, pointing, box drawing, or drawing on the image to acquire additional knowledge. It supports a variety of vision tasks (image + video recognition, OCR, diagram understanding), visual reasoning, and even 3D spatial comprehension, all in a unified multilingual framework. The model is built to work seamlessly across languages and tasks and is intended to be open sourced (including checkpoints, technical report, inference support) to encourage the community to experiment and adopt.
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    HunyuanVideo
    HunyuanVideo is an advanced AI-powered video generation model developed by Tencent, designed to seamlessly blend virtual and real elements, offering limitless creative possibilities. It delivers cinematic-quality videos with natural movements and precise expressions, capable of transitioning effortlessly between realistic and virtual styles. This technology overcomes the constraints of short dynamic images by presenting complete, fluid actions and rich semantic content, making it ideal for applications in advertising, film production, and other commercial industries.
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    Amazon Nova 2 Omni
    Nova 2 Omni is a fully unified multimodal reasoning and generation model capable of understanding and producing content across text, images, video, and speech. It can take in extremely large inputs, ranging from hundreds of thousands of words to hours of audio and lengthy videos, while maintaining coherent analysis across formats. This allows it to digest full product catalogs, long-form documents, customer testimonials, and complete video libraries all at the same time, giving teams a single system that replaces the need for multiple specialized models. With its ability to handle mixed media in one workflow, Nova 2 Omni opens new possibilities for creative and operational automation. A marketing team, for example, can feed in product specs, brand guidelines, reference images, and video content and instantly generate an entire campaign, including messaging, social content, and visuals, in one pass.
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    OmniHuman-1

    OmniHuman-1

    ByteDance

    OmniHuman-1 is a cutting-edge AI framework developed by ByteDance that generates realistic human videos from a single image and motion signals, such as audio or video. The platform utilizes multimodal motion conditioning to create lifelike avatars with accurate gestures, lip-syncing, and expressions that align with speech or music. OmniHuman-1 can work with a range of inputs, including portraits, half-body, and full-body images, and is capable of producing high-quality video content even from weak signals like audio-only input. The model's versatility extends beyond human figures, enabling the animation of cartoons, animals, and even objects, making it suitable for various creative applications like virtual influencers, education, and entertainment. OmniHuman-1 offers a revolutionary way to bring static images to life, with realistic results across different video formats and aspect ratios.
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    LTX-2.3

    LTX-2.3

    Lightricks

    LTX-2.3 is an advanced AI video generation model designed to create high-quality videos from text prompts, images, or other media inputs while maintaining strong control over motion, structure, and audiovisual synchronization. It is part of the LTX family of multimodal generative models built for developers and production teams that need scalable tools to generate and edit video programmatically. It builds on the capabilities of earlier LTX models by improving detail rendering, motion consistency, prompt understanding, and audio quality throughout the video generation pipeline. It features a redesigned latent representation using an upgraded VAE trained on higher-quality datasets, which improves the preservation of fine textures, edges, and small visual elements such as hair, text, and intricate surfaces across frames.
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    Seedance 1.5 pro
    Seedance 1.5 Pro is a next-generation AI audio-video generation model developed by ByteDance’s Seed research team that produces native, synchronized video and sound in a single unified pass from text prompts and image or visual inputs, eliminating the traditional need to create visuals first and add audio later. It features joint audio-visual generation with highly accurate lip-sync and motion alignment, supporting multilingual audio and spatial sound effects that match the visuals for immersive storytelling and dialogue, and it maintains visual consistency and cinematic motion across multi-shot sequences including camera moves and narrative continuity. Able to generate short clips (typically 4–12 seconds) in up to 1080p quality with expressive motion, stable aesthetics, and optional first- and last-frame control, the model works for both text-to-video and image-to-video workflows so creators can animate static images or build full cinematic sequences with coherent narrative flow.
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    Ray2

    Ray2

    Luma AI

    Ray2 is a large-scale video generative model capable of creating realistic visuals with natural, coherent motion. It has a strong understanding of text instructions and can take images and video as input. Ray2 exhibits advanced capabilities as a result of being trained on Luma’s new multi-modal architecture scaled to 10x compute of Ray1. Ray2 marks the beginning of a new generation of video models capable of producing fast coherent motion, ultra-realistic details, and logical event sequences. This increases the success rate of usable generations and makes videos generated by Ray2 substantially more production-ready. Text-to-video generation is available in Ray2 now, with image-to-video, video-to-video, and editing capabilities coming soon. Ray2 brings a whole new level of motion fidelity. Smooth, cinematic, and jaw-dropping, transform your vision into reality. Tell your story with stunning, cinematic visuals. Ray2 lets you craft breathtaking scenes with precise camera movements.
    Starting Price: $9.99 per month
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    Wan2.6

    Wan2.6

    Alibaba

    Wan 2.6 is Alibaba’s advanced multimodal video generation model designed to create high-quality, audio-synchronized videos from text or images. It supports video creation up to 15 seconds in length while maintaining strong narrative flow and visual consistency. The model delivers smooth, realistic motion with cinematic camera movement and pacing. Native audio-visual synchronization ensures dialogue, sound effects, and background music align perfectly with visuals. Wan 2.6 includes precise lip-sync technology for natural mouth movements. It supports multiple resolutions, including 480p, 720p, and 1080p. Wan 2.6 is well-suited for creating short-form video content across social media platforms.
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    CogVideoX-3
    CogVideoX-3 is a video generation model with new frame generation capabilities that significantly improve image stability and clarity. It delivers superior performance when handling subjects with significant movement, better adheres to instructions, and provides more realistic simulations. It supports image, text, and start-and-end-frame inputs, with video as the output modality, making it useful across text-to-video, image-to-video, and transition-based video workflows. CogVideoX-3 can be used for advertising and marketing by inputting product images or copy to quickly generate dynamic ads in multiple styles, supporting scene transitions and realistic lighting rendering. It also supports short video creation by converting single-frame images or text scripts into smooth, naturally animated short videos, covering both realistic and 3D styles. For tourism promotion, users can upload scenic spot photos and promotional text to generate immersive short videos.
    Starting Price: $0.2 per video
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    Qwen3.5-Omni
    Qwen3.5-Omni is a next-generation, fully multimodal AI model developed by Alibaba that natively understands and generates text, images, audio, and video within a single unified system, enabling more natural and real-time human-AI interaction. Unlike traditional models that treat modalities separately, it is trained from the ground up on massive audiovisual datasets, allowing it to process complex inputs such as long audio streams, video, and spoken instructions simultaneously while maintaining strong performance across all formats. It supports long-context inputs of up to 256K tokens and can handle over 10 hours of audio or extended video sequences, making it suitable for demanding real-world applications. A key feature is its advanced voice interaction capabilities, including end-to-end speech dialogue, emotional tone control, and voice cloning, enabling highly natural conversational experiences that can whisper, shout, or adapt speaking style dynamically.
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    Wan3.0-Video
    Wan3.0-Video is an all-in-one video generation model from Qwen Cloud that unifies multiple creative capabilities in a single system, including text-to-video, image-to-video, reference-to-video, editing, replication, and driving. It supports audio, image, text, and video inputs and produces video output, allowing creators to guide generation with several types of source material instead of relying on text prompts alone. The model can generate videos up to 30 seconds long and supports omni-modal reference, giving users more flexibility when carrying visual, motion, character, or other creative cues into a new result. Wan3.0-Video can also parse files, web pages, and complex images as part of the generation workflow. Its image-to-video capabilities include first-frame and first-and-last-frame generation, making it possible to define how a sequence begins or anchor both ends of a shot.
    Starting Price: $0.05 per second
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    WaveSpeedAI

    WaveSpeedAI

    WaveSpeedAI

    WaveSpeedAI is a high-performance generative media platform built to dramatically accelerate image, video, and audio creation by combining cutting-edge multimodal models with an ultra-fast inference engine. It supports a wide array of creative workflows, from text-to-video and image-to-video to text-to-image, voice generation, and 3D asset creation, through a unified API designed for scale and speed. The platform integrates top-tier foundation models such as WAN 2.1/2.2, Seedream, FLUX, and HunyuanVideo, and provides streamlined access to a vast model library. Users benefit from blazing-fast generation times, real-time throughput, and enterprise-grade reliability while retaining high-quality output. WaveSpeedAI emphasises “fast, vast, efficient” performance; fast generation of creative assets, access to a wide-ranging set of state-of-the-art models, and cost-efficient execution without sacrificing quality.
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    Ming-Flash Omni 2.0
    Ming-Flash Omni 2.0 is a full-modal large language model from Ant Group, built on a unified multimodal architecture with “modal unity + task unity” as its core design philosophy. As part of the Ming series, it is designed to achieve cross-modal understanding and generation across text, images, audio, and video, allowing one model to see, hear, speak, and draw instead of relying on multiple specialized models. Ming-Flash Omni 2.0 follows the evolution of Ming-Light Omni and Ming-Flash Omni Preview, moving from unified architecture validation and hundred-billion-parameter scaling to a Data Scaling strategy that achieves open-source SOTA performance on multiple benchmarks. The model integrates four core capability modules: image-text understanding, video analysis, speech synthesis, and image generation or editing. For image-text understanding, Ming introduces structured knowledge graphs for fine-grained visual perception.
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    HunyuanWorld
    HunyuanWorld-1.0 is an open source AI framework and generative model developed by Tencent Hunyuan that creates immersive, explorable, and interactive 3D worlds from text prompts or image inputs by combining the strengths of 2D and 3D generation techniques into a unified pipeline. At its core, the project features a semantically layered 3D mesh representation that uses 360° panoramic world proxies to decompose and reconstruct scenes with geometric consistency and semantic awareness, enabling the creation of diverse, coherent environments that can be navigated and interacted with. Unlike traditional 3D generation methods that struggle with either limited diversity or inefficient data representations, HunyuanWorld-1.0 integrates panoramic proxy generation, hierarchical 3D reconstruction, and semantic layering to balance high visual quality and structural integrity while enabling exportable meshes compatible with common graphics workflows.
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    Kling 3.0 Omni
    Kling 3.0 Omni model is a generative video system designed to create imaginative videos from text prompts, images, or reference materials using advanced multimodal AI technology. It allows users to generate continuous video clips with flexible durations ranging from approximately 3 to 15 seconds, enabling short cinematic scenes that respond closely to prompt instructions. It supports prompt-based video generation as well as reference-based workflows, where users provide images or other visual elements to guide the subject, style, or composition of the generated scene. It improves prompt adherence and subject consistency, allowing characters, objects, and environments to remain stable throughout the generated clip while maintaining realistic motion and visual coherence. The Omni model also enhances reference-based generation so that characters or elements introduced through images remain recognizable across frames.
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    Kling O1

    Kling O1

    Kling AI

    Kling O1 is a generative AI platform that transforms text, images, or videos into high-quality video content, combining video generation and video editing into a unified workflow. It supports multiple input modalities (text-to-video, image-to-video, and video editing) and offers a suite of models, including the latest “Video O1 / Kling O1”, that allow users to generate, remix, or edit clips using prompts in natural language. The new model enables tasks such as removing objects across an entire clip (without manual masking or frame-by-frame editing), restyling, and seamlessly integrating different media types (text, image, video) for flexible creative production. Kling AI emphasizes fluid motion, realistic lighting, cinematic quality visuals, and accurate prompt adherence, so actions, camera movement, and scene transitions follow user instructions closely.
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    Reka

    Reka

    Reka

    Our enterprise-grade multimodal assistant carefully designed with privacy, security, and efficiency in mind. We train Yasa to read text, images, videos, and tabular data, with more modalities to come. Use it to generate ideas for creative tasks, get answers to basic questions, or derive insights from your internal data. Generate, train, compress, or deploy on-premise with a few simple commands. Use our proprietary algorithms to personalize our model to your data and use cases. We design proprietary algorithms involving retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to tune our model on your datasets.
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    Veo 3.1 Fast
    Veo 3.1 Fast is Google’s upgraded video-generation model, released in paid preview within the Gemini API alongside Veo 3.1. It enables developers to create cinematic, high-quality videos from text prompts or reference images at a much faster processing speed. The model introduces native audio generation with natural dialogue, ambient sound, and synchronized effects for lifelike storytelling. Veo 3.1 Fast also supports advanced controls such as “Ingredients to Video,” allowing up to three reference images, “Scene Extension” for longer sequences, and “First and Last Frame” transitions for seamless shot continuity. Built for efficiency and realism, it delivers improved image-to-video quality and character consistency across multiple scenes. With direct integration into Google AI Studio and Gemini Enterprise Agent Platform, Veo 3.1 Fast empowers developers to bring creative video concepts to life in record time.
    Starting Price: $0.15 per second
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    Seedance 2.0

    Seedance 2.0

    ByteDance

    Seedance 2.0 is ByteDance’s advanced AI video generation platform built to turn creative inputs into cinematic-quality videos. It supports text prompts, images, audio, and video, blending them into polished visuals with smooth transitions and native sound. The platform uses sophisticated multimodal and motion synthesis to preserve visual consistency and character identity across multiple scenes. Users can combine up to twelve reference assets in a single project, enabling complex storytelling without manual editing. Seedance 2.0 automatically plans camera movement and pacing, giving creators director-level control with minimal effort. The system is capable of producing high-resolution video output, including 1080p and above. Its rapid popularity highlights its ability to generate engaging animated and narrative-driven content from simple inputs.
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    Gen-3

    Gen-3

    Runway

    Gen-3 Alpha is the first of an upcoming series of models trained by Runway on a new infrastructure built for large-scale multimodal training. It is a major improvement in fidelity, consistency, and motion over Gen-2, and a step towards building General World Models. Trained jointly on videos and images, Gen-3 Alpha will power Runway's Text to Video, Image to Video and Text to Image tools, existing control modes such as Motion Brush, Advanced Camera Controls, Director Mode as well as upcoming tools for more fine-grained control over structure, style, and motion.
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    Tencent Hy

    Tencent Hy

    Tencent

    Tencent HY is a self-developed, general-purpose, and multimodal large model family developed by Tencent, built to provide enterprise-grade AI services for content products, creative production, business automation, and real-world agent workflows. It covers language, image, 3D, translation, and other modalities, combining Tencent’s self-developed large model algorithms with natural language processing and computer vision technology to support higher-quality image creation, 3D generation, and intelligent content applications. Through Tencent Hunyuan AI Studio, users can interact with the model through natural human-computer dialogue, allowing the system to understand instructions, execute tasks, help users obtain information, generate content, and explore model capabilities in a practical workspace. Tencent HY supports API calls and custom parameter settings, making the model family easier to use for developers, product teams, and enterprise applications.
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    MiniMax

    MiniMax

    MiniMax AI

    MiniMax is a global AI technology company that develops advanced multimodal foundation models and AI-powered products for individuals, developers, and enterprises. Its flagship model, MiniMax M3, combines frontier-level coding capabilities, agentic task execution, native multimodal understanding, and support for up to 1 million tokens of context through its proprietary MiniMax Sparse Attention (MSA) architecture. The company offers a comprehensive ecosystem that includes coding assistants, AI agents, video generation, speech synthesis, music generation, and developer APIs. Through products such as MiniMax Code, Hailuo AI, MiniMax Audio, Talkie, and its enterprise platform, users can automate workflows, generate content, build applications, and deploy AI-powered solutions at scale. MiniMax helps organizations and developers improve productivity, accelerate software development, and create intelligent experiences across text, audio, image, video, and music.
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    SeyftAI

    SeyftAI

    SeyftAI

    SeyftAI is a real-time, multi-modal content moderation platform that filters harmful and irrelevant content across text, images, and videos, ensuring compliance and offering personalized solutions for diverse languages and cultural contexts. SeyftAI offers a comprehensive suite of content moderation tools to help you keep your digital spaces clean and safe. Detect and filter out harmful text in multiple languages. SeyftAI's API makes it easy to integrate our content moderation capabilities into your existing applications and workflows. Detect and filter out harmful or explicit images with zero human intervention. Easily integrate SeyftAI's content moderation capabilities. Tailor our content moderation workflows to your specific needs. Access detailed reports and analytics on your content moderation activities. A real-time, multi-modal content moderation platform that filters harmful and irrelevant content across text, images, and videos, ensuring compliance.
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    Kling 2.6

    Kling 2.6

    Kuaishou Technology

    Kling 2.6 is an advanced AI video generation model that produces fully immersive audio-visual content in a single pass. Unlike earlier AI video tools that generated silent visuals, Kling 2.6 creates synchronized visuals, natural voiceovers, sound effects, and ambient audio together. The model supports both text-to-audio-visual and image-to-audio-visual workflows for fast content creation. Kling 2.6 automatically aligns sound, rhythm, emotion, and camera movement to deliver a cohesive viewing experience. Native Audio allows creators to control voices, sound effects, and atmosphere without external editing. The platform is designed to be accessible for beginners while offering creative depth for advanced users. Kling 2.6 transforms AI video from basic visuals into fully realized, story-driven media.
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    Wan2.2-Animate
    Wan2.2 Animate is a specialized module within the Wan video generation framework designed for high-fidelity character animation and character replacement, enabling users to transform static images into dynamic videos or swap subjects within existing footage while preserving realism and motion consistency. It works by taking two primary inputs: a reference image that defines the character’s appearance and a reference video that provides motion, expressions, and scene context. Using this combination, it can animate a still character by replicating body movements, gestures, and facial expressions from the source video, or replace the original subject in a video while maintaining the original lighting, camera movement, and environment for seamless integration. It relies on advanced techniques such as spatially aligned skeleton signals and implicit facial feature extraction to accurately reproduce motion and expressions.
    Starting Price: $5 per month
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    Gen-4.5

    Gen-4.5

    Runway

    Runway Gen-4.5 is a cutting-edge text-to-video AI model from Runway that delivers cinematic, highly realistic video outputs with unmatched control and fidelity. It represents a major advance in AI video generation, combining efficient pre-training data usage and refined post-training techniques to push the boundaries of what’s possible. Gen-4.5 excels at dynamic, controllable action generation, maintaining temporal consistency and allowing precise command over camera choreography, scene composition, timing, and atmosphere, all from a single prompt. According to independent benchmarks, it currently holds the highest rating on the “Artificial Analysis Text-to-Video” leaderboard with 1,247 Elo points, outperforming competing models from larger labs. It enables creators to produce professional-grade video content, from concept to execution, without needing traditional film equipment or expertise.
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    Runway Aleph
    Runway Aleph is a state‑of‑the‑art in‑context video model that redefines multi‑task visual generation and editing by enabling a vast array of transformations on any input clip. It can seamlessly add, remove, or transform objects within a scene, generate new camera angles, and adjust style and lighting, all guided by natural‑language instructions or visual prompts. Built on cutting‑edge deep‑learning architectures and trained on diverse video datasets, Aleph operates entirely in context, understanding spatial and temporal relationships to maintain realism across edits. Users can apply complex effects, such as object insertion, background replacement, dynamic relighting, and style transfers, without needing separate tools for each task. The model’s intuitive interface integrates directly into Runway’s existing Gen‑4 ecosystem, offering an API for developers and a visual workspace for creators.
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    Wan2.1

    Wan2.1

    Alibaba

    Wan2.1 is an open-source suite of advanced video foundation models designed to push the boundaries of video generation. This cutting-edge model excels in various tasks, including Text-to-Video, Image-to-Video, Video Editing, and Text-to-Image, offering state-of-the-art performance across multiple benchmarks. Wan2.1 is compatible with consumer-grade GPUs, making it accessible to a broader audience, and supports multiple languages, including both Chinese and English for text generation. The model's powerful video VAE (Variational Autoencoder) ensures high efficiency and excellent temporal information preservation, making it ideal for generating high-quality video content. Its applications span across entertainment, marketing, and more.
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    Wan2.7-T2V

    Wan2.7-T2V

    Alibaba

    Wan2.7-T2V is Qwen Cloud’s text-to-video model for generating cinematic videos from text prompts, with synchronized audio and multi-shot storytelling built into one workflow. It produces videos from 2 to 15 seconds long at 720P or 1080P resolution and supports aspect ratios including 16:9, 9:16, 1:1, 4:3, and 3:4. Wan2.7 is designed for stronger narrative performance, delivering more nuanced and organic emotional depth in story arcs, visceral impact in action sequences, and rhythmic cinematic cuts for greater storytelling power. Developers can describe multiple shots directly inside a prompt using timed scene segments, while the model maintains the main subject across transitions. The model also supports custom audio input for synchronized video generation, letting creators incorporate narration, dialogue, music, or other sound into the result. Prompts can be up to 5,000 characters, giving teams room to define detailed scenes, camera framing, character actions, atmosphere, pacing, etc.
    Starting Price: $0.1 per second
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    GLM-4.5V

    GLM-4.5V

    Zhipu AI

    GLM-4.5V builds on the GLM-4.5-Air foundation, using a Mixture-of-Experts (MoE) architecture with 106 billion total parameters and 12 billion activation parameters. It achieves state-of-the-art performance among open-source VLMs of similar scale across 42 public benchmarks, excelling in image, video, document, and GUI-based tasks. It supports a broad range of multimodal capabilities, including image reasoning (scene understanding, spatial recognition, multi-image analysis), video understanding (segmentation, event recognition), complex chart and long-document parsing, GUI-agent workflows (screen reading, icon recognition, desktop automation), and precise visual grounding (e.g., locating objects and returning bounding boxes). GLM-4.5V also introduces a “Thinking Mode” switch, allowing users to choose between fast responses or deeper reasoning when needed.
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    Gemini 3 Deep Think
    The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows.
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    Hunyuan T1

    Hunyuan T1

    Tencent

    ​​Hunyuan T1 is Tencent's deep-thinking AI model, now fully open to all users through the Tencent Yuanbao platform. This model excels in understanding multiple dimensions and potential logical relationships, making it suitable for handling complex tasks. Users can experience various AI models on the platform, including DeepSeek-R1 and Tencent Hunyuan Turbo. The official version of the Tencent Hunyuan T1 model will also be launched soon, providing external API access and other services. Built upon Tencent's Hunyuan large language model, Yuanbao excels in Chinese language understanding, logical reasoning, and task execution. It offers AI-based search, summaries, and writing capabilities, enabling users to analyze documents and engage in prompt-based interactions.
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    Kling 3.0

    Kling 3.0

    Kuaishou Technology

    Kling 3.0 is an advanced AI video generation model built to produce cinematic-quality videos from text and image prompts. It delivers smoother motion, sharper visuals, and improved physical realism for more lifelike scenes. The model maintains strong character consistency, ensuring stable appearances and controlled facial expressions throughout a video. Enhanced prompt comprehension allows creators to design complex scenes with dynamic camera angles and fluid transitions. Kling 3.0 supports high-resolution outputs that meet professional content standards. Faster rendering speeds help teams reduce production timelines significantly. The platform enables high-quality video creation without relying on traditional filming or expensive production tools.