Kluster.ai's Innovative Cost Control Methodology
Kluster.ai reconstructs the economic model of AI reasoning through a multi-dimensional cost optimization strategy. The core technology lies in its intelligent time window algorithm, which is capable of automatically scheduling tasks based on fluctuations in global computing resource prices. The platform adopts a compute-storage separation architecture, and users only need to pay for the actual reasoning hours consumed. Measurement data shows that the cost of batch processing 1 million text NLP tasks is only $1.2, which is 33% of traditional cloud services. the system provides cost prediction function, which can estimate the total cost of the project based on historical data. The prepaid credit model supports additional discounts on quarterly committed usage. The unique resource sharing pool mechanism increases the idle arithmetic utilization rate to 95%. Comparison tests show that Kluster.ai's annualized cost is 67% lower than AWS SageMaker for the same workload on a continuous basis.
- Billing model: according to the actual reasoning hours billing
- Savings: 671 TP3T cost reduction over traditional program
- Added value: intelligent budget forecasting + resource sharing
This answer comes from the articleKluster.ai: low-cost AI inference platform, sends 100$ DeepSeek-R1 credits, ~167 million tokens!The
