MINIMAX-WP(0100.HK)：模型智能持续突破 解锁商业化潜能

Core Viewpoint - The company has actively revised its logic regarding "DAU/traffic = barrier," recognizing that the only moat in the AI era is the intellectual advantage of models. By reducing inefficient ToB sales teams and C-end user acquisition costs, resources are intensely focused on high-intensity model research and technological breakthroughs. This "anti-consensus" contraction is essentially a strategic move to gain an edge in the second half of the Scaling Law, focusing on reasoning and architectural innovation. The management team possesses top-tier research and ToB commercialization and delivery experience [1]. Industry Transformation - AI is defining a new generation of productivity, with the Total Addressable Market (TAM) shifting from software budgets to labor budgets. The industry is undergoing a qualitative change from discriminative AI to generative AI. The Scaling Law is driving exponential improvements in model intelligence while reasoning costs are decreasing exponentially, making AI not just a traditional SaaS "tool" but a "digital employee" with reasoning and planning capabilities. For instance, the traditional software market targets about $300 billion of IT budgets, while AI, as a production factor, is expected to penetrate a global labor cost market of approximately $13 trillion [1]. Technical Evolution - The technical path is evolving, with increasing engineering barriers and a gradual consolidation of model frameworks. The extensive pre-training Scaling (computational power/data) is facing diminishing marginal returns, leading the industry into a new phase of "architectural innovation & reasoning-side Scaling." Companies like DeepSeek (MLA/architecture compression) and Google (multimodal association) represent different technical breakthrough directions, with technical barriers returning to a combination of "engineering capability + architectural innovation" [2]. Company Advantages - The MiniMax team benefits from a founder with both research capabilities and ToB delivery experience. The founder, Yan Junjie, previously served as Vice President of SenseTime and CTO of the Smart City Business Group, demonstrating exceptional technical and management skills. Under his leadership, a team of over 700 achieved industry-leading facial recognition algorithms, with the smart city business generating over 2 billion RMB in revenue in 2021, targeting government and large enterprises with a focus on engineering delivery. Unlike the mobile internet era, the management team understands that "user scale ≠ model intelligence." Therefore, the company's strategic focus is shifting from "revenue generation/user acquisition" to "technological iteration" by 2025 [3]. Financial Projections - The company expects to achieve revenues of $80 million, $185 million, and $351 million for FY25-27, representing year-on-year growth of 162%, 131%, and 90%. AI-native product revenues (To C) are projected to be $58 million, $139 million, and $263 million, with growth exceeding 140%. Open platform revenues (ToB) are expected to be $22 million, $46 million, and $88 million. As reasoning costs optimize and high-margin ToB business stabilizes, Non-GAAP gross profits are projected to be $20 million, $74 million, and $193 million, corresponding to Non-GAAP gross margins of 25.0%, 40.0%, and 55.0%. Despite ongoing competition in computational power, Non-GAAP net losses are expected to narrow, recording losses of -$240 million, -$180 million, and -$80 million for FY25-27, with a significant trend of decreasing loss rates [4]. Investment Logic - Within the AI sector, the investment logic between the "infrastructure layer (e.g., DeepSeek)" and the "native application layer" is diverging. Compared to DeepSeek, which establishes barriers on the cost side through architectural innovation, MiniMax's deep focus on multimodal (voice/video) interaction experience provides a stronger moat in user stickiness and commercialization. The integration of "high-sensory interaction" and "productivity tools" is key, with the former (Talkie/Xingye) providing vast RLHF data and the latter (Hailuo/open platform) generating high-margin cash flow. Greater revaluation potential lies in the technological unlocking in the second half of the Scaling Law. As the company's strategic focus returns to technological research, new multimodal models (e.g., Video-01, end-to-end voice) are expected to significantly contribute to incremental ARR starting in FY26-27 [5].