Why AI Server Demand Is Set to Explode by 2025 – Key Trends and Market Drivers

Evolution of Server Platforms

Servers have progressed through four stages to meet emerging workloads: general‑purpose servers, cloud servers, edge servers, and finally AI servers, which rely on GPUs to boost parallel computation capabilities.

AI Server Workloads

AI servers are categorized by application scenario into training and inference machines. Training workloads demand higher chip compute power. According to IDC, the share of inference compute demand is expected to rise to 60.8 % by 2025 as large‑model applications proliferate.

Chip Configurations and Cost Structure

Typical AI server architectures combine CPUs with accelerators such as GPUs, FPGAs, or ASICs. In China, the CPU+GPU combination dominates the market, accounting for 91.9 % of deployments. The cost of an AI server is largely driven by its chips, which represent 25 %–70 % of the total bill‑of‑materials; for training‑focused servers, more than 80 % of the cost comes from CPUs and GPUs.

Compute Demand Forecasts

ARK Invest estimates that GPT‑4 contains up to 15 trillion parameters, implying a peak compute requirement of roughly 31,271 PFLOP/s·day . As vendors worldwide accelerate the development of trillion‑parameter models, training demand is expected to keep rising, while the rapid growth of inference workloads further fuels the overall compute revolution.

Geopolitical and Supply‑Chain Factors

The United States has restricted sales of Nvidia’s high‑performance A100 and H100 GPUs to China. Nvidia’s China‑specific A800 variant, which reduces interconnect bandwidth, is currently the most viable substitute.

Domestic GPU Competition

Chinese GPU manufacturers such as HaiGuang Information and BiRui Technology have released single‑card solutions whose performance approaches that of Nvidia’s offerings, especially in inference scenarios where they demonstrate competitive capabilities.

Market Share and Vendor Landscape

Chinese AI server manufacturers collectively hold **over 35 %** of the global market, with Inspur leading the segment. Each domestic vendor possesses distinct strengths, and they are poised to benefit from increasing downstream demand for AI compute.

Source

The analysis is based on the report “大模型算力：AI服务器行业（2023）”.