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The AI Infrastructure Decision Matrix: How to Choose Between Cloud GPUs, Dedicated Servers, Colocation, and Hybrid Designs
The AI Infrastructure Decision Matrix: How to Choose Between Cloud GPUs, Dedicated Servers, Colocation, and Hybrid Designs
By infiniti.network.service

Executive Summary: Choosing the right AI hosting layer is no longer a simple price comparison between cloud and bare metal. The real decision depends on workload shape, data gravity, network latency, compliance, and operational maturity. Cloud GPUs are excellent for bursty experimentation and rapid scaling. Dedicated GPU servers usually win for steady inference, predictable performance, […]

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Sizing GPUs for 70B-Class LLM Inference: Memory, Throughput, Architecture, and Cost
Sizing GPUs for 70B-Class LLM Inference: Memory, Throughput, Architecture, and Cost
By infiniti.network.service

For most 70B-class dense LLMs, the practical GPU choice is determined less by raw compute than by memory headroom for weights, KV cache, and concurrency. A single 80GB GPU can serve a heavily quantized deployment, but BF16 or FP16 inference usually needs multi-GPU tensor parallelism or a larger-memory accelerator. The correct answer depends on quantization, […]

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