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HappyHorse video model shows promise but lags behind competitors like Seedance 2.0

A recent evaluation of the HappyHorse video generation model indicates it performs adequately but falls short of competitors like Seedance 2.0 and Kelin 3.0. While HappyHorse boasts a larger parameter count and advanced features such as 15-second narrative capabilities and 1080p upscaling, its output in terms of cinematic quality and prompt adherence is considered less refined. Industry experts suggest that HappyHorse's performance may be limited by the quality of its training data, particularly in short-form and professional film content, leading to a highly competitive and homogenized market for video generation models. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT HappyHorse's performance suggests the video generation market is highly competitive, with incremental improvements becoming standard.

RANK_REASON This is an evaluation of a specific video generation model, comparing its capabilities against existing products.

Read on 36氪 (36Kr) →

COVERAGE [1]

  1. 36氪 (36Kr) TIER_1 中文(ZH) ·

    Without a technological leap, there is only catching up

    HappyHorse的技术能力究竟如何? 内容科技公司三生清影自研的工具Glowave已经接入了HappyHorse,在深入体验了该大模型之后,创始人姜奕祺对该模型的评价是,表现不错,但略逊于Seedance2.0。 姜奕祺毕业于清华大学计算机视觉专业,曾在阿里达摩院任职,对视频大模型了解颇深。他向36氪表示,相较于Seedance2.0,HappyHorse的影视感与提示词还原上有所不足。具体来讲,前者指的是更接近传统专业影视表现的效果,包括画面的精细度、背景的丰富度等。后者可以简单粗暴的理解为,听懂人话的能力。 36氪也测评了Seedance2.0、