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导语：近日，雷峰网获悉，高品质 AI Token 生产服务商趋境科技（Approaching.AI）完成 B 轮融资，本轮融资金额超13亿人民币；今年内已累计募得24
近日，雷峰网(公众号：雷峰网)获悉，高品质 AI Token 生产服务商趋境科技（Approaching.AI）完成 B 轮融资，本轮融资金额超13亿人民币；今年内已累计募得24亿人民币。多项核心经营指标在半年内实现超十倍速增长，持续获得产业和资本的高度认可。
本轮融资由浙财创新、萧山资本、工银投资、中关村科学城、星连资本及钱江世纪城共同领投。云创资本、湖南高新纵横、建投华科、申万创新投、中信聚信、珠海科技产业集团、商汤科技、网宿科技、甘肃树帜、常金控、元智未来、清证星竹、小咖资本等跟投，老股东尚势资本继续追投。
这是继今年 7 月完成 A 轮融资后，趋境科技短期内再获大额融资。截至今年10月，趋境科技已在 2026 年连续完成多轮融资。密集的资本跟进背后，既反映出市场对 AI 基础设施赛道长期价值的共识，更源于投资人对趋境科技战略聚焦、技术领先和商业化交付成绩等综合实力的肯定——过去半年，趋境科技不但全面跑通了从技术架构到规模化商业交付的全链路，更是持续引领推理行业的技术演进，以技术创新推动了国产算力的性能大跃升。
本轮募集的资金将重点投向高品质 AI Token 产能扩张、ATaaS（Approaching.AI Token as a Service）平台升级迭代、推理底层技术和新产品的研发，以及商业化合作与交付体系完善等方面。
投资者说 · 浙财创新董事长陈栋
“随着 AI 产业走向规模化应用，推理效率、成本与系统优化能力正成为商业化的重要基础。趋境科技在大模型推理领域具备持续的技术积累和工程交付能力。我们期待与公司长期同行，共同推动高效、普惠的 AI 基础设施建设与规模化应用。”
投资者说 · 萧山资本集团董事长祝利烽
“趋境科技是萧山布局 AI Infra 的标杆项目。早在行业聚焦训练时，公司便前瞻深耕推理赛道。依托清华系团队十余年的技术积累与自研 ATaaS 平台，将算力高效转化为可规模化生产的高品质 AI Token，推动国产算力进入核心生产环节。双方正携手推进万卡级人工智能 Token 工厂建设，加速形成‘芯模联动’产业闭环。萧山资本将以长期资本、耐心资本深度赋能，支持其把高品质 AI Token 工厂能力快速复制，为 AI 产业高质量发展注入持久动力。”
投资者说 · 星连资本创始管理合伙人张鸣晨
“星连资本自2024年天使轮成为股东以来，一路见证趋境科技在技术、产品、服务、战略和商业化等全方位不断创造远超预期的佳绩；更是在不到三年的时间里已经快速跃升为 AI 推理领域耀眼的一流企业。这也是星连资本在过往每一轮都持续大额追加投资的根本原因。我们看好趋境科技从技术与商业验证走向规模化建设和持续运营后的广阔成长空间，也期待陪伴团队持续引领 AI 推理行业的发展。”
从“粗放供给”到“品质服务”
｜高品质 AI Token 成为行业新风向
Token 市场发展初期，行业供给侧多“重 Token 数、轻服务品质”，以粗放扩量的方式快速做大供给规模。彼时大模型尚处在试点验证阶段，未深度嵌入企业核心生产链路，业务对性能、稳定性、模型质量的容错空间较大，这类供给模式得以被市场接纳。而趋境科技自创立之初，便坚持锚定生产级推理标准，持续投入推理系统原始创新，夯实工程底座，在行业内率先定义高品质 AI Token 服务理念。
趋境科技所定义的“高品质 AI Token”：锚定生产级场景，提供高智能、低时延、高速率、强稳定，兼具规模化交付能力与可控综合成本的 AI Token 服务。
伴随产业重心转向 Agent 驱动的业务闭环落地，大模型逐步承载生产级核心流程，AI 推理行业正迎来范式转变：企业对 AI Token 的智能水平、响应时延、输出速度、上下文完整性、服务稳定性提出了严苛的生产级刚性要求。这一转变与趋境一直以来坚持和倡导的高品质AI Token 服务理念不谋而合。
产业拐点显现，Token 市场快速形成清晰的品质分层：“可用即可”的粗放供给已难以匹配生产场景诉求，兼顾多维指标平衡的高品质 AI Token 供给稀缺、需求激增，成为市场刚需。作为高品质 AI Token 服务最早的布局者和深耕者，趋境科技凭借长期沉淀的推理系统底层技术与工程化能力，持续推进高品质 AI Token 服务的规模化交付。趋境科技现已成为高品质 AI Token 服务领域的领航者。
立足“少模型、深优化、高品质”
｜加速高品质 AI Token 规模化交付
高品质 AI Token 能够持续规模化交付，最终取决于两个核心命题：单位算力效能能否持续提升，规模化供给能力能否稳定增长。
围绕这一目标，为兑现高品质 AI Token 的生产标准，趋境坚持“少模型、深优化、高品质”的技术路线，聚焦市场需求明确、应用广泛的主流大模型，持续推进“异构推理”“以存换算”“虚实同构”等多项全球首创技术的工程落地，专注企业生产场景的高品质 AI Token 需求。
“少模型、深优化”解决的是“同一批算力能够生产多少高品质 AI Token”，稳定生产负载和跨集群运营解决的是“这些算力有多少时间真正处于有效工作状态”。“少模型”本身并不天然带来更高的利用率，只有单位算力产出和有效利用率同时提升，AI Token 业务的单位经济才有可能成立。
这一路线背后的商业逻辑非常明确：企业级客户最终为业务结果付费，而不是为模型兼容数量付费。
目前，趋境科技已经形成一套可复制的高品质 AI Token 工厂建设与运营模式：既有日均数万亿级 Token 产能的已投产项目，也有面向区域产业生态与头部客户的战略合作及在建布局。更重要的是，整体业务已经跨过成本线。以真实业绩验证了 ATaaS 平台的大规模交付与持续运营能力。
技术创新重构国产算力体系
｜性价比超越国际最领先算力
让国产算力能够支撑高品质 AI Token 的生产是趋境科技一直以来的目标。
面对国内外芯片的性能差异，趋境科技探索出一条以系统级技术创新实现算力效率突破的新路径，先后率先提出了“国产 Prefill-Decode（PD）异构协同”“高性能异构 KV Cache 转换”“异构算力计算融合”等一系列创新技术方案，重构国产算力计算模式和推理体系，并已在高标准生产场景中正式投产。
在真实生产级环境中，实现国产芯片承载万亿级头部大模型，并达成高品质 AI Token 规模化生产，同时整体性价比超越国际最领先算力。
趋境首创的异构协同推理技术，在保障模型输出质量、响应速度和服务稳定性的前提下，以更低的硬件投入实现更高的有效 Token 产出，稳定承接头部客户的真实业务需求。
这一突破具备双重开创性价值：在商业层面，构筑差异化核心技术护城河，为趋境规模化共建高品质 AI Token 工厂打开增长天花板，支撑业绩与资本价值持续跃升；在产业战略层面，有助于跳出单纯比拼硬件参数的技术竞争，重新定义国产算力价值标尺，让分散在全国、不同架构的国芯资产释放足额推理产能，为国家搭建自主可控、供给充沛、具备商业经济性的 AI 推理底座提供可落地的核心工程方案，进一步夯实我国大模型产业链安全与算力自主根基。
以技术拓产量
｜半年实现业绩十倍跃升
持续自主技术创新，是驱动趋境科技高品质 AI Token 产量实现指数级增长的核心动力。
半年来，伴随多项首创技术持续推出与工程打磨，公司平均单台算力的 AI Token 生产效率逐月攀升，持续引领行业；高品质 AI Token 日均产量增长超过百倍，并攀升至超万亿量级，年内业务收入已达到去年全年近十倍。
在产业格局上，趋境科技正推动 AI 基础设施从传统算力资源供给向高品质 AI Token 规模化生产与运营升级。依托 ATaaS 平台及 Token 工厂建设运营能力，公司在半年内携手产业伙伴推进十余个日均万亿级 AI Token 工厂项目，推动国产算力规模化应用，联合地方国资、产业龙头及生态伙伴，构建连接算力基础设施、大模型与行业应用的新型 AI Token 供给网络。
区域化基础设施布局
公司以河南、杭州、海南为重点，结合区域资源与产业需求，推进高品质 AI Token 生产与服务网络建设。在河南推进与地方国资联合运营，协同开展 Token 生产、销售与客户消纳；华东区域总部落地杭州钱江世纪城，规划建设万卡级 Token 工厂，服务长三角企业级推理需求；在海南探索地方国资建设、趋境提供平台与运营服务的合作模式。通过因地制宜的建设运营模式，推动算力投入转化为可持续的 Token 供给能力，带动本地运营能力与产业生态发展。
产业生态与共建共营
公司与商汤科技、并行科技、弘信电子、网宿科技、摩尔线程、沐曦股份、天数智芯等企业达成生态合作，推动高品质 AI Token 工厂建设与运营，探索基于国产芯片的高品质 AI Token 生产技术方案，共建自主可控的国产 AI 算力生态。携手商汤推进日均十万亿级 Token 工厂建设，共建产线已具备日均万亿级 Token 的生产与稳定消纳能力；联合并行科技打造日均万亿级 Token 工厂，打通算力基础设施、推理优化、标准化 Token 供给与产业应用全链路；与弘信电子完成其旗下燧弘华创无锡、厦门两大 Token 工厂的技术适配与试点落地；携手网宿科技，结合其全球分布式边缘资源与网络能力，开展推理优化和智能调度协同，提升高品质 AI Token 的生产效率与交付稳定性。
持续释放的技术效率红利，推动业务与资本同步迈入高速增长周期。融资节奏与业绩增长同频，年内多轮交割有序落地，保持平均两月一轮的节奏，单轮募资规模环比持续走高；今年内累计募资总额达24亿人民币，获得国资、产业资本与市场化机构持续重仓。系列融资落地后，股东结构进一步多元成熟，汇聚地方国资、金融资本、头部产业集团与一线市场化机构，为后续区域算力共建、国产异构生态协同、大规模行业交付提供坚实支撑。
顶尖科研与开源筑基
｜构筑系统级长期工程壁垒
商业化进展背后，是趋境科技在科研、开源工程与企业级生产交付方面的持续积累。
从前沿的技术探索到严苛的工程落地，贯穿始终的是一支兼具学术高度与产业经验的核心团队：公司管理团队由创始人兼 CEO 艾智远博士、总裁兼 CFO 武文洁博士、CTO 陈祥麟等组成，共同推进技术研发、资本协同、产业合作与项目交付；在技术研究层面，郑纬民院士担任首席科学顾问，武永卫教授担任首席科学家，为公司底层技术演进提供学术与技术支持；章明星副教授担任董事，指导技术战略与关键研发工作，推动前沿研究与工程实践衔接。
学术研究之外，趋境科技核心团队长期参与大模型推理开源生态建设，团队牵头发起 KTransformers，并参与 Mooncake 的发起与共建，为相关研究提供了面向不同模型、硬件和负载条件的工程验证环境，也推动团队围绕“全系统异构协同”“以存换算”“虚实同构”等方向持续探索。
从学术研究和开源工程出发，相关技术能力进一步沉淀至 ATaaS 平台，并在 AI Token 工厂的真实业务负载中持续检验。秉持“算力更高效、智能更普惠”的理念，趋境科技以真实需求牵引生产投入，以长期交付检验技术能力，正通过 ATaaS 平台和 AI Token 工厂，输出高品质 AI Token 的标准化生产体系，重塑 AI 推理供给范式，赋能千行百业生产级智能化升级。
趋境科技 CEO 艾智远表示：在算力转化为高质量生产力的赛跑中，真正的稀缺壁垒不是规模，而是单位能效与商用交付能力。过去半年，趋境科技以超十倍速的业务增长证明了“少模型、深优化、高品质”路线的巨大商业潜能。资本的持续加注，是对趋境科技业务交付成绩的肯定。面向未来，趋境科技将依托本轮资金加速产能扩张，深化国产 PD 异构方案落地，以更稳定、更高效、更具成本效率的高品质 AI Token 服务支持客户规模化应用，推动国产异构资源更充分地进入真实生产场景，与产业伙伴共同构建多元、稳定、可持续的 AI 推理供给体系。
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Quality AI Token Production Services Convergence (Approaching.AI)
In recent days, the Ray Peak Network (WeChat Official Account: Thunder Peak Network) has been informed that the High-Quality AI Token Production Services Convergence Technology (Approaching.AI) has completed the B round of financing, which amounts to over 1.3 billion yuan, which has accumulated over the course of this year. A number of core business indicators have grown at a rate of more than 10 times in six months and have continued to enjoy high industry and capital recognition.
The current round of financing was co-financed by Zhefu Innovation, Xiaoshan Capital, the Bank of China and China Bank Investment, the Science City of Central Guanamura, the Star Company Capital and Chan Gang Century City. The old shareholders continue to invest in capital.
This is the short-term time after the completion of the A round of financing in July of this year, in the short term, a significant amount of additional financing will be available for convergence technology. By October of this year, Convergence Technology had completed successive rounds of financing in 2026. Behind intensive capital follow-up, both the market's consensus on the long-term value of AI infrastructure tracks and the investor's recognition of the combined power of convergence technology strategy focus, technology leadership and commercial delivery performance - – Over the past six months, convergence technology has not only made its way across the entire chain from technological architecture to scaled-up commercial delivery, but has also continued to lead the technological evolution of the reasoning industry, with technological innovation driving the performance of national production.
The funds raised in this round will focus on high-quality AI Token capacity expansion, the upgrading of the Ataas (Approaching.AI Token as a Service) platform, the research and development of low-level technologies and new products, and the improvement of commercialization cooperation and delivery systems.
The investor said...
“As the AI industry moves towards a scaleed application, reasoning efficiency, cost and system optimization are becoming an important basis for commercialization. Convergence technology has continued technology accumulation and engineering delivery in the field of LLM reasoning. We look forward to working with companies on a long-term basis to promote efficient and inclusive AI infrastructure development and scale-up.”
The investor says...
“Technology is a pamphlet project for Xiaoshan layout AI Infra. As early as the industry focused on training, the company was looking ahead to the deep-drop reasoning track. Based on more than 10 years of technological accumulation and self-study of the AtaaS platform by the Qinghua team, this translates high-quality AI Token, which is capable of scalable production, into a core production chain. The two sides are working together to advance the construction of the Vanka-class artificial intelligence Token plant and to accelerate the formation of a `chipmolix' industrial closure. Shaw Hill Capital will be empowered with long-term, patient capital depth to support its rapid replication of high-quality AI Token plant capabilities and to inject a lasting impetus into the high-quality development of AI industries.”
Investors say...
“Stellar capital, since the Angel Wheel became a shareholder in 2024, has been a witness to the continuous creation of far better-than-anticipated performances in technology, products, services, strategies and commercialization across the board; much more so in less than three years, it has rapidly jumped into a top-notch enterprise in the field of AI reasoning. This is also the underlying reason why the capital of the Star Company has continued to make significant additional investments in each of the previous rounds. We look forward to moving from technological and commercial validation to a vast growth space for scale-building and continuous operation, and to accompanying the team to continue to lead the development of the AI reasoning industry.”
From "broad supply" to "quality services"
High quality AI Token became the new industry.
In the early days of the Token market, the supply side of the industry was heavily “heavy” token, light service quality, which was rapidly scaled up in a broad-scale manner. At other times, LLM was still in the pilot validation phase, was not deeply embedded in the enterprise ' s core production chain, and there was greater room for error in performance, stability, model quality and such modes of supply were accepted by the market. From the very beginning of its existence, it has adhered to the criteria of anchoring production-level reasoning, continuing to invest in original innovation in the reasoning system, building on the engineering base and taking the lead in defining the high-quality AI Token service concept within the industry.
“High Quality AI Token” as defined by Convergence Technology: anchoring production-level scenarios that provide high intelligence, low latency, high speed, strong stability, and AI Token services with both scale delivery capabilities and manageable combined costs.
As the focus of industry shifts to the Agent-driven business closed ground, LLM gradually carries the production-level core process, and the AI reasoning industry is moving towards a paradigm shift: firms impose stringent production-level requirements for AI Token ' s intelligence level, latency, output speed, context ' s integrity, and service stability. This shift coincides with the high-quality AI Token service concept that has been upheld and advocated in the past.
The industrial boom has shown that the Token market has quickly developed a clear quality layer of “as far as possible” provisioning that is difficult to match with production landscape demands, and that the high-quality AI Token supply, which is balanced by multi-dimensional indicators, is scarce, demand has surged and has become market demand. As a high-quality AI Token service provider and deep-droper, Trend Technology, with its long-settled, deduced system ' s downside technical and engineering capabilities, continues to advance the scaling-up of the high-quality AI Token service. Trend technology has become a pilot in the high-quality AI Token service.
Based on “minus models, deep optimization, high quality”
|Accelerating high quality AI Token scale delivery
The ability of high-quality AI Token to continue to scale delivery ultimately depends on two core propositions: the continued improvement of unit computing efficiency and the steady growth of scalable supply capacity.
With this objective in mind, in order to achieve high-quality AI Token production standards, there has been a convergence towards a “less model, more optimized, more high-quality” technical route, focusing on the clear market demand and the wide-ranging application of mainstream LLM, and the continuous advancement of “isomeric reasoning” to land on many of the world's pioneer technologies, such as the “false equivalent” of convert, focusing on the high-quality AI Token needs of the enterprise production landscape.
“Little models, deep optimization” addresses “how much high-quality AI Token can be produced by the same calculus”, and “how much time do these algorithms actually work effectively” by stabilizing production loads and cross-cluster operations. The “less models” themselves did not naturally lead to higher utilization rates, and the unit economy of AI Token operations could be established only if unit output and effective utilization were increased at the same time.
The business logic behind this route is very clear: business-level clients end up with paid, rather than model-compatible Z105Z.
Convergence technology has now developed a replicable high-quality AI Token plant construction and operation model: it consists of several hundred billion class Token production projects per day, strategic cooperation with regional industrial ecology and head clients, and ongoing construction. More importantly, the overall business has crossed the cost line. The large-scale delivery and sustainability of the Ataas platform was validated with real performance.
Technological innovation to reshape national production systems
It's worth more than the world's leading figure.
To enable the country to sustain high-quality AI Token production is a long-standing goal of convergence technology.
In the face of the differences in the performance of domestic and foreign chips, convergence technology has explored a new path to a calculus-efficiency breakthrough with system-level technological innovation, leading to a series of innovative technology options such as the “Nationally produced Prefil-Decode (PD) Isomer Convergence”, the “High Performance Isomer KV Cache conversion”, the “Insistence of Isomer Calculus”, the recasting of the system of computational and reasoning for national production and the formal commissioning of production in high-standard production scenarios.
In a real production-level environment, a trillion-class head of LLM is carried on a national chip, and high-quality AI Token is produced on a scale, while overall value for money exceeds international lead.
The first of these isomeric synergetic techniques, with a lower hardware input to achieve more effective Token output and stabilize the real business needs of head-to-head clients, while safeguarding the quality of model output, response speed and service stability.
This breakthrough is of double pioneering value: at the commercial level, the construction of a core moat of differentiated technologies, the creation of a high-quality, high-quality, growth ceiling for the scale of the movement, the AI Token plant, the support of performance and the continued leap in capital value; at the strategic level of industry, it helps to emerge from technical competition over mere hardware parameters, redefines the country ' s calculator of the value of production, allows the release of full and reasoned productive capacity from national core assets scattered across the country and over different structures, and provides the country with a viable core engineering programme for a controlled, well-supplyed, commercially-economic base of reasoning, and further strengthens our country ' s LLM industrial chain of safety and calculation.
To expand production with technology
Ten times more in six months.
Sustained and autonomous technological innovation is a central driver of high-quality AI Token production growth.
Over the past six months, the company's average single-desk computing efficiency, AI Token, has risen monthly and continues to lead the industry; high-quality AI Token has grown by more than a hundred times the average daily output and has risen to over trillions of tons, with annual operating income nearly ten times the year.
In terms of industry patterns, convergence technology is driving the upgrading of AI infrastructure from the supply of traditional computing resources to high-quality AI Token scale production and operations. Building on the operational capacity of the AtaaS platform and the Token factory, the company has been working with industry partners to promote over a dozen 100 billion-a-day AI Token factory projects over a six-month period, to promote the scaling-up of national production and to build a new AI Token supply network of connectivity infrastructure, LLM and industry applications.
Regionalized infrastructure layout
Focusing on Henan, Hangzhou and Hainan, the company promotes high-quality AI Token production and service networks, combining regional resource and industrial needs. Promotion of joint operations with local state finance in Henan, in collaboration with Token Production, Sales and Client Disbursement; planning for the construction of the Vanka class Token factory in Hangzhou, China Regional Headquarters in Changzhou, to serve the long triangular enterprise-level reasoning needs; exploration of cooperation models in Hainan for local state finance, convergence, platform delivery and operational services. Local capacity for operations and industrial ecology are promoted by building business models adapted to local conditions to facilitate the transformation of computing inputs into sustainable Token supply capacity.
Industrial ecology and joint construction
The company works in ecological cooperation with businesses such as business soup technology, parallel technology, Hongsung electronics, Internet-based technology, moor circuits, musaka shares, and day-to-day brain cores to promote the construction and operation of high-quality AI Token factories and explore high-quality AI Token production technologies based on national chips, and to build autonomous and controlled national production AI computing ecology. Together, it promotes the construction of 100 trillion-grade Token plants per day, with the co-production and stabilization of 100 billion-grade Token production and reduction capacity; it works with parallel technologies to create hundreds of trillion-grade Token plants per day, with a full chain of computing infrastructure, reasoning optimization, standardization of Token supply and industrial applications; it completes the technical adaptation and piloting of the two main plants, Hongshin and Shinmen; and it combines web-based technology, with its global distributed marginal resources and network capacity, to develop reasoning optimization and smart scheduling synergies to enhance high-quality AI Token production efficiency and delivery stability.
The technology efficiency dividend that continues to be released drives business and capital back into a high growth cycle. The pace of financing has been the same as the growth in performance, with multiple rotations during the year, maintaining an average of two-monthly rounds, and single-cycle fund-raising has continued to grow at a higher scale than ever; the cumulative total of fund-raising this year amounts to RMB 2.4 billion, with a continuing backlog of access to State capital, industrial capital and market institutions. With the fall of the portfolio of financing, the stockholders structure has become more diversified and mature, bringing together local state capital, financial capital, front-line industrial groups and front-line market institutions to provide a solid support for subsequent regional co-financing, national heteogeneological synergy, and large-scale industry delivery.
Top-of-the-art research and the foundation of open sources
Long-term engineering barriers to building systems
Behind the advances in commercialization is the continued accumulation of convergence technologies in research, open-source engineering and enterprise-level production delivery.
From cutting-edge technology exploration to hard engineering landings, it has been a core team with academic and industrial experience: The company management team, consisting of the founder and CEO of the CEO, Dr. Ei Ji-Yi, President and President of the CFO Wu Wengjie, and CTO Chen Xiaoqing, is working together to advance technology R & D, capital synergies, industrial cooperation and project delivery; at the technical research level, Zheng Laijiang is the chief scientific adviser, and Professor Wu Yongwei is the chief scientist, providing academic and technical support for the company ' s bottom technological evolution; and Zhang Star Associate Professor is a director to guide technology strategy and key research and development work and to promote the interface between forward research and engineering practices.
In addition to academic research, the Core Team on Convergence Technology has long been involved in the LLM reasoning-open-source ecological construction, led by KTransformers and co-founded by Mooncake, providing an engineering validation environment for different models, hardware and load conditions for the research, and facilitating the team's ongoing exploration around the direction of “system-wide isomer synergy” “to store convert” “false contours”.
From academic research and open-source engineering, the relevant technical capabilities are further deposited on the Ataas platform and continuously tested in the real operational load of the AI Token plant. In keeping with the concept of “more efficient, more intelligent and more inclusive” technology, which leads to the production of inputs with real demand for long-term delivery of technical capabilities, a standardized production system of high-quality AI Token is being exported through the Ataas platform and the AI Token factory, remodelling the AI reasoning supply paradigm and enabling the upgrading of production-grade intelligence in a wide range of industries.
GEO Ei Jiji says that in the race for arithmetic to high-quality productivity, the real and scarce barrier is not size, but unit energy efficiency and commercial delivery. Over the past six months, the business growth of convergence technology at a rate exceeding ten times the rate has demonstrated the great commercial potential of the “less models, more refined, higher quality” route. The continued investment in capital is a recognition of the achievements in the delivery of the science and technology business in convergence. For the future, convergence technology will depend on the current round to accelerate the expansion of production capacity, deepen the PD isomeric programme of national production to land it to support more stable, efficient, and cost-effective, high-quality client size applications, promote fuller access to real production scenes for domestic production isomer resources, and work with industry partners to construct a pluralistic, stable and sustainable AI reasoning supply system.
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