Computing Power Matching and Reselling P Diagram

Strengths

• Light-asset operation, eliminating the need to build large-scale reusable IDC R&D from scratch.
• Flexible token billing methods lower the barrier to entry for AI entrepreneurs.
• Efficiently aggregates societal idle computing power resources, enhancing industry-wide computing power utilization.

Weaknesses

• Core product supply is extremely passive and vulnerable to upstream fluctuations from Nvidia and major cloud vendors.
• Focuses on scale over profits; requires heavy early-stage investment and short-term losses to expand supply and demand volume.
• Low technical barriers, relying heavily on business relationships and susceptible to replacement by self-built internal networks.

Opportunities

• With the 4 trillion RMB computing power infrastructure established, the token industry becomes a new track trend in 2026.
• Nvidia or major hardware computing power manufacturers' 'computing power for revenue share' well supports secondary distribution communities.
• Large-scale landing of AI applications leads to a genuine explosion in B-side refined computing power cost demand.

Threats

• Cloud giants (Alibaba, major tech firms) launch their own token factory products, launching a dimensional reduction strike via consecutive price wars.
• Increased transparency in token prices causes matching spreads to approach zero, leading to a collapse of the margin model.
• Stricter cryptocurrency regulations spill over into virtual asset matching markets such as computing power.