HappyHorse-1.0 is a mysterious AI video generation model that recently claimed the #1 spot on the Artificial Analysis Video Arena leaderboard. Submitted pseudonymously without a verifiable team identity, this 15B parameter unified Transformer features a 40-layer architecture that jointly denoises text tokens, image latents, video tokens, and audio tokens in a single sequence. The model supports both text-to-video (T2V) and image-to-video (I2V) generation with native multilingual audio synthesis for Chinese, English, Japanese, Korean, German, and French—all produced in one unified forward pass without cross-attention mechanisms.
이 컬렉션의 마무리 작업을 진행 중입니다 — 그동안 아래의 유사한 컬렉션을 살펴보세요.
Seedance 2.0(by Bytedance) is a multimodal video generation model that redefines "controllable creation," moving beyond the limitations of text or start/end frames. It supports quad-modal inputs—text, image, video, and audio—and introduces an industry-leading "Universal Reference" system. By precisely replicating the composition, camera movement, and character actions from reference assets, Seedance 2.0 solves critical issues with character consistency and physical coherence, empowering creators to act as true "directors" with deep control over their output.
HappyHorse-1.0 is a mysterious AI video generation model that recently claimed the #1 spot on the Artificial Analysis Video Arena leaderboard. Submitted pseudonymously without a verifiable team identity, this 15B parameter unified Transformer features a 40-layer architecture that jointly denoises text tokens, image latents, video tokens, and audio tokens in a single sequence. The model supports both text-to-video (T2V) and image-to-video (I2V) generation with native multilingual audio synthesis for Chinese, English, Japanese, Korean, German, and French—all produced in one unified forward pass without cross-attention mechanisms.
Launching this March, Wan2.7 is the latest powerhouse in the Qwen ecosystem, delivering a massive upgrade in visual fidelity, audio synchronization, and motion consistency over version 2.6. This all-in-one AI video generator supports advanced features like first-and-last frame control, 3x3 grid synthesis, and instruction-based video editing. Outperforming competitors like Jimeng, Wan2.7 offers superior flexibility with support for real-person image inputs, up to five video references, and 1080P high-definition outputs spanning 2 to 15 seconds, making it the premier choice for professional digital storytelling and high-end content marketing.
Google DeepMind’s Veo 3.1 represents a paradigm shift in AI video generation, empowering creators with director-level narrative control and cinematic-grade audio quality that seamlessly integrates with its enhanced visual realism. By bridging the gap between imaginative concepts and photorealistic execution, this advanced model offers a transformative solution for a wide range of application scenarios, from professional filmmaking and high-end advertising to immersive digital content creation.
The GPT Image Family is OpenAI's latest suite of multimodal image generation and editing models, built on the powerful GPT architecture. This family includes three tiers — GPT Image-1, GPT Image-1.5, and GPT Image-1 Mini — each available in both Text-to-Image and Image-to-Image variants. Combining GPT's world-class language understanding with DALL·E-class visual synthesis, these models deliver exceptional prompt adherence, photorealistic rendering, and creative versatility across illustration, photography, design, and visualization tasks. The series offers flexible pricing and quality tiers to match any workflow — from rapid prototyping and high-volume content production to professional-grade final deliverables. Whether you need ultra-fast iterations at minimal cost or maximum quality for brand campaigns, the GPT Image Family has a solution tailored to your needs.
Nano Banana 2 (by Google), is a generative image model that perfectly balances lightning-fast rendering with exceptional visual quality. With an improved price-performance ratio, it achieves breakthrough micro-detail depiction, accurate native text rendering, and complex physical structure reconstruction. It serves as a highly efficient, commercial-grade visual production tool for developers, marketing teams, and content creators.
Seedream 5.0, developed by ByteDance’s Jimeng AI, is a high-performance AI image generation model that integrates real-time search with intelligent reasoning. Purpose-built for time-sensitive content and complex visual logic, it excels at professional infographics, architectural design, and UI assistance. By blending live web insights with creative precision, Seedream 5.0 empowers commercial branding and marketing with a seamless, logic-driven workflow that turns sophisticated data into stunning, high-fidelity visuals.
Kuaishou’s flagship video generation suite, Kling 3.0, features two powerhouse models—Kling 3.0 (Upgraded from Kling 2.6) and Kling 3.0 Omni (Kling O3, Upgraded from Kling O1)—both offering high-fidelity native audio integration. While Kling 3.0 excels in intelligent cinematic storytelling, multilingual lip-syncing, and precision text rendering, Kling O3 sets a new standard for professional-grade subject consistency by supporting custom subjects and voice clones derived from video or image inputs. Together, these models provide a comprehensive solution tailored for cinematic narratives, global marketing campaigns, social media content, and digital skit production.
GLM is a cutting-edge LLM series by Z.ai (Zhipu AI) featuring GLM-5, GLM-4.7, and GLM-4.6. Engineered for complex systems and long-horizon agentic tasks, GLM-5 outperforms top-tier closed-source models in elite benchmarks like Humanity’s Last Exam and BrowseComp. While GLM-4.7 specializes in reasoning, coding, and real-world intelligent agents, the entire GLM suite is fast, smart, and reliable, making it the ultimate tool for building websites, analyzing data, and delivering instant, high-quality answers for any professional workflow.
Explore OpenAI’s language and video models on Atlas Cloud: ChatGPT for advanced reasoning and interaction, and Sora-2 for physics-aware video generation.
Seedream 4.5, developed by ByteDance’s Jimeng AI, is a versatile, high-fidelity model that unifies creative generation with precise image editing. Engineered for professional consistency and intricate text rendering, it excels at multi-subject fusion, brand identity, and high-resolution marketing assets. By bridging spatial logic with artistic control, Seedream 4.5 empowers designers with a seamless, instruction-driven workflow that transforms complex concepts into polished, commercial-grade visuals.
Vidu, a joint innovation by Shengshu AI and Tsinghua University, is a high-performance video model powered by the original U-ViT architecture that blends Diffusion and Transformer technologies. It delivers long-form, highly consistent, and dynamic video content tailored for professional filmmaking, animation design, and creative advertising. By streamlining high-end visual production, Vidu empowers creators to transform complex ideas into cinematic reality with unprecedented efficiency.
Atlas Cloud는 업계 최고의 최신 크리에이티브 모델을 제공합니다.
ingle self-attention architecture with modality-specific projections in the first/last 4 layers and shared parameters across the middle 32 layers for seamless multimodal generation.
Ranked #1 in both Text-to-Video (Elo 1333) and Image-to-Video (Elo 1392) on Artificial Analysis Video Arena, surpassing Dreamina Seedance 2.0 by 60 and 37 points respectively.
Native support for six languages (Chinese, English, Japanese, Korean, German, French) with claimed ultra-low WER lip-synchronization.
Generates dialogue, ambient sounds, and Foley effects alongside video in a single pass through unified token denoising—no separate audio pipeline required.
One unified model handles both text-to-video and image-to-video tasks, appearing under the same model name in both arena categories.
Self-reported speeds of ~2 seconds for 5-second clips at 256p and ~38 seconds at 1080p on H100 hardware (unverified by third parties).
이 모델 패밀리로 구축할 수 있는 실용적인 사용 사례와 워크플로를 발견하세요 — 콘텐츠 제작과 자동화부터 프로덕션급 애플리케이션까지.
The HappyHorse-1.0 API enables studios and creators to generate cinematic video content that achieved #1 rankings on the Artificial Analysis Video Arena leaderboard. Leveraging its 15B parameter unified architecture, the API delivers leaderboard-winning quality with natural motion and synchronized audio across six languages. Perfect for advertising agencies, film pre-visualization, and premium content creators requiring uncompromising video quality—when the model becomes publicly available.
For global brands and international creators, the HappyHorse-1.0 API generates video content with native audio in six languages including Chinese, English, Japanese, Korean, German, and French. It excels at producing culturally relevant content with claimed ultra-low WER lip-synchronization. This use case fits global marketing teams and international social media campaigns requiring authentic multilingual output.
The HappyHorse-1.0 API allows marketers and influencers to rapidly produce engaging short-form video content with automatic audio generation. By processing creative concepts into polished video clips with synchronized sound including dialogue and Foley effects, it creates scroll-stopping content optimized for TikTok, Instagram Reels, and YouTube Shorts.
몇 분 만에 시작하세요 — 간단한 단계를 따라 Atlas Cloud 플랫폼을 통해 모델을 통합하고 배포하세요.
atlascloud.ai에서 가입하고 인증을 완료하세요. 신규 사용자는 플랫폼 탐색과 모델 테스트를 위한 무료 크레딧을 받습니다.
고급 Happy Horse 1.0 모델과 Atlas Cloud의 GPU 가속 플랫폼을 결합하여 비교할 수 없는 성능, 확장성 및 개발자 경험을 제공합니다.
낮은 지연 시간:
실시간 추론을 위한 GPU 최적화 추론.
통합 API:
하나의 통합으로 Happy Horse 1.0, GPT, Gemini 및 DeepSeek를 실행합니다.
투명한 가격:
Serverless 옵션을 포함한 예측 가능한 token당 청구.
개발자 경험:
SDK, 분석, 파인튜닝 도구 및 템플릿.
신뢰성:
99.99% 가동 시간, RBAC 및 규정 준수 로깅.
보안 및 규정 준수:
SOC 2 Type II, HIPAA 준수, 미국 내 데이터 주권.
As of April 2026, HappyHorse-1.0 is not publicly accessible. There is no public API, no downloadable weights, no documented pricing, and no SLA. The model exists as a leaderboard entry with verified quality signals from blind user votes, but practical access does not exist yet. Watch for GitHub repository releases, HuggingFace model cards, or API announcements to know when it becomes available.