SenseNova - filings, earnings calls, financial reports, news

SenseNova

Search documents

Ren Min Ri Bao· 2025-07-03 00:10

Core Insights - MiniMax, a Shanghai-based AI company, has launched the world's first open-source large-scale hybrid architecture inference model, MiniMax-M1, which ranks second globally among open-source models [1] - The company has also released video generation model Hailuo 02, which achieved 300 million views within a week of its release on social media [1][6] - MiniMax distinguishes itself by not following mainstream dense architectures and traditional attention mechanisms, focusing instead on AGI since before the rise of ChatGPT [1][8] Performance and Cost Efficiency - The competition in large models is shifting from mere parameter scale to efficiency, cost, and overall implementation capabilities [2] - M1 supports an impressive context input of 1 million tokens, comparable to Google's latest closed-source model Gemini 2.5 Pro, while its reinforcement learning phase cost only $535,000 [2] - Hailuo 02 directly competes with Google's third-generation video generation model Veo3, showcasing superior performance in generating coherent and logical video sequences [3] Innovation in AI Video Generation - Hailuo 02 has pioneered a new category of AI video called "Animal Olympics" [4] - The development of Hailuo 02 involved collaboration with a diverse team of directors, screenwriters, and artists to ensure high-quality output [5] - High-quality data, innovative algorithms, and meticulous training processes are cited as key factors in the success of Hailuo 02 [6] Strategic Positioning - MiniMax remains one of the few startups still committed to foundational model research amidst a trend of major companies reducing their efforts in this area [7] - The company is exploring "sparse activation" MoE architecture to reduce computational costs, diverging from the prevalent dense architecture approach [8] - MiniMax aims to stay competitive in the long-term race of large model development, collaborating with other major players in Shanghai's AI ecosystem [9]

中金 | AI智道（9）：多模态推理技术突破，向车端场景延伸

中金点睛· 2025-06-02 23:45

文 / 于钟海 , 魏鹳霏 , 肖楷 , 赵丽萍中金研究以MiniMax V-Triune新框架成果为例，推理感知统一框架在可拓展性、泛化性初步验证。 V-Triune以三层组件架构实现视觉推理和感知任务统一至强化学习框架：1）多模态样本数据格式化；2）验证器奖励计算，采用异步客户端-服务器架构，奖励计算和主训练循环解耦；3）数据源级指标监控，便于溯源和提升稳定性。结合动态IoU奖励机制、冻结ViT参数等工程优化，Orsta系列模型（32B参数）在MEGA-Bench Core基准测试中实现了最高14.1%的性能提升。多模态推理助力智能驾驶能力升阶。在智能驾驶场景，多模态推理是增强道路交通标志识别判断能力、提升复杂场景泛化性的重要途径，正成为头部智能驾驶企业算法演进的重点。2025年5月30日，蔚来世界模型NVM首个版本正式开启推送，具备全量理解、想象重构和推理能力，能够对实时环境多模信息进行理解和推演，在选择最优ETC车道通行、停车场自主寻路等场景的性能提升显著。此外，理想自研的VLA大模型亦具备思维链推理能力，以多模态推理模拟人类驾驶员的思维运作方式。图表1：MiniMax多模态RL ...