Understand compute,
make better choices
Read the KONST team's technical views on GPU selection, cost evaluation, and AIDC planning.
Showing 7 articles
How Many GPUs Does an Enterprise Need?
Estimate GPU requirements from model memory, input and output tokens, peak request rate, latency targets, benchmark capacity, and redundancy.
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How Taiwanese Enterprises Should Choose an AI Implementation Partner
Compare AI consultants, application teams, model governance platforms, infrastructure providers, and system integrators by business need, deliverables, integration, operations, and total cost.
Who Operates an AI Data Center? GPU Cluster vs. Traditional IT Operations
Compare GPU cluster and conventional server operations across monitoring, troubleshooting, change management, recovery, security, and 24/7 responsibilities.
How to Choose GPU Bare-Metal Rental in Taiwan: H100, H200, B200, and B300
Compare H100, H200, B200, and B300 for GPU bare-metal rental in Taiwan, including memory, delivery models, pricing, benchmarks, and SLA considerations.
How Enterprises Should Choose GPU Compute: Cloud, Bare Metal, Clusters, or AIDC
Compare GPU Cloud, bare-metal rental, leasing, dedicated clusters, colocation, and AIDC construction by workload, control, and full cost.
AWS vs GCP vs GPU Cloud vs NeoCloud: An Enterprise AI Compute Comparison
Compare AWS, GCP, GPU Cloud, and NeoCloud by integration, GPU capacity, cluster networking, data movement, operations, SLA, and exit cost.
AI Data Centers vs Traditional Data Centers: AIDC Planning and Design
Learn how AI data centers differ from traditional facilities across power, cooling, rack density, floor loading, GPU topology, networking, and storage.
Plan the next stage of compute together
Where Efficiency Leads.
Where AI Defines the Future.