InBev Cloud AI Arithmetic

Still worrying about the lack of computing power and uncontrolled cost for large model training? Is the construction, operation and maintenance of the enterprise’s intelligent computing center complicated and the idle arithmetic power is seriously wasted? The emergence of IBM Cloud AI computing power (core brand of IBM Numerical Science, a subsidiary of IBM Corporation) has provided a highly efficient solution – as the leading intelligent computing power full-link service platform in China, it takes the industry’s first “effective computing power cost per unit” evaluation system as the core, covering the entire scenario of computing center construction, operation and maintenance, GPU container service, scientific research empowerment, etc. As the leading intelligent computing center construction, operation and maintenance, GPU container service, scientific research empowerment and other scenes, it has become the first choice of universities, small and medium-sized enterprises, and large enterprises in 2025 by virtue of its high-performance hardware clusters, elastic scheduling capabilities and cost-effective advantages. This article combines the latest official developments and actual test information to disassemble its core value and application scenarios, and take you to unlock the new paradigm of efficient computing power use.

First, the platform positioning: to break the arithmetic pain points of the “smart computing ecological builder”.

The core mission of IBM Cloud is to “make computing power more efficient and inclusive”, with a clear positioning and significant differentiation:

• Core Users: Technology enterprises requiring large-scale training, universities and institutes pursuing low-cost research, small and medium-sized enterprises (SMEs) lacking computing power resources, and IDC organizations with idle computing power;
• Core value: through standardized products and innovative evaluation system, it solves the three major industry pain points of low arithmetic utilization, difficult to measure cost, and complicated construction, operation and maintenance;
• Underlying support: Integration of NVIDIA HGX-H800/A800, 4090 and other top hardware, with self-developed parallel storage and cluster scheduling system, forming a “hardware + software + service” of the whole chain of intelligent computing solutions.

In December 2024, InBev Cloud firstly mentioned the innovative index of “effective arithmetic cost per unit” in AICON Beijing, through the three-dimensional evaluation of “card availability + card utilization + model arithmetic utilization (MFU)”, subverting the traditional evaluation mode of only looking at the hardware investment, and allowing the arithmetic efficiency to be measured by the evaluation mode of only looking at the hardware investment. Through the three-dimensional evaluation of “card availability rate, card utilization rate, and model force utilization rate (MFU)”, it subverts the traditional evaluation mode of only looking at hardware inputs, and provides a scientific standard for the measurement of arithmetic efficiency. As of November 2025, the Jingneng Intelligent Computing Center project has been set up to serve more than 30 universities, including Tsinghua University and Renmin University of China, and has become the core arithmetic support for collaborative innovation among industries, universities and research institutes.

Second, the core advantages of the actual test: 5 highlights to reconstruct the arithmetic service experience

1. Top Computing Power Cluster: Covering all scenarios of computing power demand.

IBM Cloud provides a full range of computing power from single machine to 10,000 card level, with industry-leading hardware configuration:

• Flagship training cluster: NVIDIA HGX-H800/A800 (8-card cluster, 80GB video memory on a single card, 256-core CPU + 2TB memory), adapting to large-scale training of GPT-5, Qwen 3 and other large models.
• Elastic reasoning nodes: NVIDIA 4090 (8-card cluster, 24GB video memory), A40 (8-card cluster, 48GB video memory), to meet the needs of reasoning for pendant models and SMEs lightweight.
• Basic arithmetic node: NVIDIA A16 (32-card cluster, 16GB video memory), adapting to low-threshold scenarios such as image recognition and data processing.

All nodes are equipped with high-speed RDMA network and NVMe SSD storage, and the measured efficiency of multi-card parallel training is 30% higher than that of ordinary clusters, and the model training cycle is 25% shorter.

2. Innovative Evaluation System: Make Arithmetic Cost More Controllable

The core competitiveness of IBM Cloud is “effective cost per unit of computing power”, which can effectively reduce ineffective expenditures:

• Core Logic: Accurately account for the actual effective arithmetic cost by improving card availability (to reduce failure and downtime), card utilization (to avoid idle resources), and MFU (to optimize model operation efficiency);
• Industry value: solving the pain point of traditional arithmetic service “only counting the installed cost, not counting the actual benefit”, after a technology company uses it, the effective arithmetic cost is reduced by 42%;
• Transparent management: the background real-time display of the three major indicators of data, users can intuitively monitor the utilization of arithmetic power, targeted optimization.

3. Full-stack product matrix: full coverage from construction to realization.

IBM Cloud has built four core product segments, which have been tested and adapted to the needs of different users:

• Smart Computing Center Construction and Operation and Maintenance: Provides standardized and modularized construction solutions, including parallel storage, cluster monitoring, and automatic fault recovery system, which has landed on the Jingneng project and supports 10,000-card-level cluster delivery;
• GPU Container Service: elastic K8s cluster, second start/stop, per minute billing, support SSH/Kubectl management, built-in predefined image and model library, university research team test environment configuration time shortened from 1 day to 10 minutes.
• Advanced Arithmetic Lab: Focusing on arithmetic performance evaluation, it provides enterprises with model optimization and hardware adaptation solutions to help improve MFU;
• Arithmetic power stationing platform: IDC organizations can set up idle arithmetic power, set the price and specifications independently, and obtain stable income through the platform, and the efficiency of realizing idle arithmetic power has increased by 60%.

4. Deep integration of industry, academia and research: exclusive support for scientific research and teaching.

For universities and scientific research institutions, Infocloud has launched customized services with outstanding support:

• Scientific research arithmetic fueling package: provide free/low-cost arithmetic support for AI academic projects, the first batch of selected projects in 2025 has helped many papers on NeurIPS 2025; and the first batch of selected projects in 2025 has helped many papers on NeurIPS 2025.
• Teaching Exclusive Program: After the introduction of Shushu Normal University, the course “Comprehensive Practice of Artificial Intelligence Systems” has realized that 100% of the students have completed the MMDet visual model training, cracking the problem of lack of traditional teaching arithmetic.
• Resource sharing: integrating commonly used datasets and model libraries, supporting cross-institutional knowledge sharing, and increasing the efficiency of research team collaboration by 40%.

5. Safe, stable and flexible: enterprise-level service guarantee.

In the real test, IBM Cloud performs brilliantly in security and flexibility:

• Security Compliance: Passed Equal Protection Level 3 certification, supports data encryption and fine-grained authority control to meet the needs of sensitive scenarios such as finance and government affairs;
• High Availability: Distributed deployment + automated fault recovery, with a measured annual availability rate of 99.9%, avoiding training interruption losses;
• Flexible Expansion: Seamless expansion from standalone to 10,000 card level, support for on-demand increase or decrease in computing power, SMEs do not need to invest in high hardware costs at once.

Typical application scenarios: covering the whole field of industry, academia and research.

1. Large model training and reasoning

• Technology enterprises: use HGX-H800 cluster to train general-purpose large models, or deploy industry pendant model reasoning services based on 4090 nodes, with 50% lower cost than self-built clusters;
• Startup teams: quickly validate model prototypes through GPU container services, billed by the minute to avoid idle waste.

2. Higher education research and teaching

• Scientific research projects: AI algorithm innovation is carried out with the help of “arithmetic power refueling package”, which supports parallel training of multiple cards and helps thesis publication and technological breakthroughs;
• Practical teaching: Provide universal computing power for AI-related courses, allowing students to participate in model training practice with zero threshold, Shou Normal University and Minjiang College have already cooperated.

3. Enterprise digital transformation

• Manufacturing industry: using arithmetic for production data modeling, quality inspection image analysis, and improving production efficiency;
• Financial industry: support risk assessment models, customer behavior analysis through arithmetic to achieve intelligent decision-making.

4. Idle Arithmetic Realization

• IDC organizations and enterprises: through the arithmetic stationed on the platform shelves idle GPU resources, independent management of prices and inventory, stable monthly passive income, measured idle arithmetic utilization rate increased from 30% to 85%.

Comparison with Similar Platforms: Core Competitiveness is Highlighted

Data source: Compiled from actual measurements and official information in November 2025

V. Use of the process and guide to avoid pitfalls

1. Quick Start Steps

• Individual/enterprise users (arithmetic leasing): register an account → select the arithmetic specifications (container service/bare metal) → configure the mirror and parameters → start nodes → billing according to the actual hours of use, support shutdown at any time;
• IDC organization (arithmetic cash): qualification audit → official Agent automatically detects hardware → set specifications and prices → shelve arithmetic → get revenue, real-time view of details in the background.

2. Efficient use of recommendations

• Model selection: choose HGX-H800/A800 for large model training and 4090/A40 for reasoning to avoid “big horse and small car”.
• Cost optimization: start training during off-peak hours, and make use of the elastic capacity expansion function to avoid occupying arithmetic power for a long time;
• Research application: university teams can apply for the “arithmetic power refueling package” to reduce research costs;
• Troubleshooting: 24/7 technical support is available for problems, and the cluster supports automatic fault recovery without manual intervention.

Summarize: the cost-effective choice in the new era of computing power.

With the core advantage of “top hardware, innovative evaluation system, full-stack service, and industry-academia-research empowerment”, the AI arithmetic of InBev Cloud breaks the many pain points of traditional arithmetic services, so that users of different sizes can enjoy efficient, controllable, and inclusive arithmetic support. Whether it is large model training for science and technology enterprises, scientific research and teaching in colleges and universities, or idle arithmetic cash for IDC organizations, they can all find precisely adapted solutions.

With the continuous evolution of AI technology, Ebtech Cloud will deepen the domestic arithmetic adaptation and industry solutions to further reduce the threshold of arithmetic use. Visit the official website ( ebtech.com ) to inquire about cooperation and apply for a trial of arithmetic power, unlocking the efficient arithmetic experience brought by the “unit effective arithmetic cost”, and letting arithmetic power truly become the core driving force of innovation.