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市场调查报告书
商品编码
1883964
Frost Radar：大规模语言模型与多模态生成式人工智慧平台的基础架构，2025 年Frost Radar: Foundational LLMs and Multimodal GenAI Platforms, 2025 |
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基准化分析体系：创新驱动新交易与成长通路的拓展
生成式人工智慧领域面临着一项根本性的挑战：如何在史无前例的变革中，将底层模式的突破性力量转化为现实世界的价值。大型语言模式（LLM）和多模态人工智慧工具的爆炸性成长，可望彻底改变从企业生产力到创造性工作的方方面面，但各组织机构在可靠性、扩充性和投资回报率（ROI）方面仍面临诸多挑战。策略挑战显而易见：必须以广泛可用、可靠且安全的方式利用这些技术，否则将面临在下一代数位创新中落后的风险。
强大的力量正在颠覆产业格局，重塑主导和方法。创新的速度令人惊嘆。就在几年前，1750亿参数的模型还被视为最先进的技术；而如今，规模更大、效率更高的模型层出不穷，最先进的标准也从单纯的规模转向了质量。至关重要的是，开源与封闭式开发之间的竞争正在重新定义产业动态。虽然专有大型语言模型（LLM）仍在不断突破性能极限，但开放原始码模型正在迅速缩小差距。这种开放模型的趋势透过吸引全球开发团体参与，加速了创新进程，甚至使新创公司也能以远低于传统成本的价格建立Start-Ups的LLM。结果是，混合策略正迅速成为主流，市场也随之快速发展。
要展现领导地位，生成式人工智慧平台必须在多个领域表现卓越。仅仅拥有「最聪明」的模型是不够的。首先，技术优势仍然是基石。顶级平台提供先进的人工智慧功能（推理、创造力、多语言、多模态理解），并具备标竿级的效能。同样重要的是企业级特性：强大的安全性和合规性功能、对资料和模型输出的精细控制，以及在混合云端或本地环境中部署以保护隐私的能力。适应性也是一项关键特性。领导企业提供用于使用自身资料微调模型的工具、用于整合到任何软体的API，以及针对常见用例的预先建置解决方案库。真正市场领先的平台还会培育一个充满活力的生态系统，透过丰富的文件、社群支援和插件/扩展框架来吸引开发者、整合商和第三方应用程式。
弗若斯特沙利文公司根据一系列特定要求，遴选出此次弗若斯特雷达™分析报告中的12家公司。这些要求包括：开发并交付具有影响力的基础模型；透过商业部署或参与开放原始码社群展现显着的市场吸引力；明确致力于推动多模态能力；以及对更广泛的企业和消费者人工智慧生态系统产生切实的影响。这些公司之所以能在众多竞争者中脱颖而出，是因为它们在前沿人工智慧研究方面投入巨资，平台具备服务数百万用户的扩充性，并且在支援下一代人工智慧驱动型应用方面具有重要的战略意义。
弗若斯特沙利文公司对产业内的众多公司进行分析。根据领导力及其他特征筛选出的公司将接受进一步分析，并根据10项成长和创新标准进行基准测试，以确定其在弗若斯特雷达™上的位置。该报告会考虑每家公司的优势以及与这些优势最契合的机会，从而在弗若斯特雷达™上呈现其竞争格局。
目录
策略问题与成长环境
Frost Radar™：底层大规模语言模型与多模态生成式人工智慧平台
Frost Radar™：值得关注的公司
- Alibaba
- Anthropic
- Baidu
- Cohere
- DeepSeek
- Meta
- Mistral
- OpenAI
- Reka AI
- Tencent
- xAI
Frost Radar™：支撑大规模语言模型和多模态生成式人工智慧平台，2025 年
最佳实践和成长机会
- 最佳实践
- 发展机会
Frost Radar™ 分析
未来工作：利用 Frost Radar™ 加强关键相关人员的能力
- 登上 Frost Radar™ 的意义
- Frost Radar™协助CEO成长团队
- Frost Radar™ 为投资者赋能
- Frost Radar™ 为客户赋能。
- Frost Radar™ 为电路板赋能
免责声明
Frost Radar™：底层大规模语言模型 (LLM) 与多模态生成式人工智慧平台，2025 年
A Benchmarking System to Spark Companies to Action - Innovation That Fuels New Deal Flow and Growth Pipelines
The generative AI sector faces a defining challenge: how to translate the breakthrough power of foundation models into real-world value amid unprecedented disruption. An explosion of large language models (LLMs) and multimodal AI tools promises to transform everything from enterprise productivity to creative work, yet organizations grapple with trust, scale, and ROI. The strategic imperative is clear: harness these technologies in a way that is broadly accessible, reliable, and secure, or risk falling behind in the next era of digital innovation.
Powerful forces are disrupting this landscape, reshaping who leads and how. The pace of innovation is staggering. Only a few years ago, a 175-billion-parameter model was cutting-edge; today, even larger or more efficient models are emerging, and the frontier is shifting to quality over sheer size. Crucially, an open vs. closed development battle is redefining industry dynamics. Proprietary LLMs still push performance boundaries, but open-source models have rapidly narrowed the performance. This open-model wave is accelerating innovation trajectories by engaging a global developer community, even enabling start-ups to build competitive LLMs at a fraction of the usual cost. The result is a fast-evolving market where hybrid strategies prevail.
To demonstrate leadership, a generative AI platform must excel on multiple fronts. It's not just about having the "cleverest" model. First, technical superiority remains foundational: top platforms deliver advanced AI capabilities (reasoning, creativity, multilingual fluency, and multimodal understanding) with benchmark-setting performance. Equally important are enterprise-grade attributes: robust security and compliance features, granular control over data and model outputs, and the ability to deploy in hybrid cloud or on-prem environments for privacy. Adaptability is another hallmark. Leaders offer tools for fine-tuning models on proprietary data, APIs for integrating into any software, and libraries of pre-built solutions for common use cases. A true market-leading platform also cultivates a thriving ecosystem, attracting developers, integrators, and third-party applications via strong documentation, community support, and plugin/extension frameworks.
Frost & Sullivan selected the 12 companies profiled in this Frost Radar™ analysis based on their ability to meet a set of specific criteria, including the development and delivery of influential foundational models, demonstration of significant market traction through either commercial adoption or open-source community engagement, a clear commitment to advancing multimodal capabilities, and a tangible impact on the broader enterprise and consumer AI ecosystem. These companies stand out from the larger group because of their investment in frontier AI research, their ability to scale their platforms to serve millions of users, and their strategic importance in powering the next generation of AI-driven applications.
Frost & Sullivan analyzes numerous companies in an industry. Those selected for further analysis based on their leadership or other distinctions are benchmarked across 10 Growth and Innovation criteria to reveal their position on the Frost Radar™. The publication presents competitive profiles of each company on the Frost Radar™ considering their strengths and the opportunities that best fit those strengths.
Table of Contents
Strategic Imperative and Growth Environment
Frost Radar™: Foundational LLMs and Multimodal GenAI Platforms
Frost Radar™: Companies to Action
- Alibaba
- Anthropic
- Baidu
- Cohere
- DeepSeek
- Meta
- Mistral
- OpenAI
- Reka AI
- Tencent
- xAI
Frost Radar™: Foundational LLMs and Multimodal GenAI Platforms, 2025
Best Practices & Growth Opportunities
- Best Practices
- Growth Opportunities
Frost Radar™ Analytics
Next Steps: Leveraging the Frost Radar™ to Empower Key Stakeholders
- Significance of Being on the Frost Radar™
- Frost Radar™ Empowers the CEO's Growth Team
- Frost Radar™ Empowers Investors
- Frost Radar™ Empowers Customers
- Frost Radar™ Empowers the Board of Directors
Legal Disclaimer
Frost Radar™: Foundational LLMs and Multimodal GenAI Platforms, 2025
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