Tag: LLM deployment

Infrastructure Requirements for Serving Large Language Models in Production
Infrastructure Requirements for Serving Large Language Models in Production

Tamara Weed, Feb, 17 2026

Serving large language models in production requires specialized hardware, smart software, and careful architecture. Learn the real costs, GPU needs, and deployment strategies that work today.

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Science & Research

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LLM infrastructure GPU requirements LLM deployment production AI model serving
Memory Footprint Reduction: Hosting Multiple Large Language Models on Limited Hardware
Memory Footprint Reduction: Hosting Multiple Large Language Models on Limited Hardware

Tamara Weed, Feb, 4 2026

Discover how memory footprint reduction techniques enable businesses to deploy multiple large language models on single GPUs. Learn about quantization, parallelism, and real-world applications saving costs while maintaining accuracy.

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Science & Research

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memory optimization LLM deployment model quantization GPU efficiency multi-model hosting
Multi-GPU Inference Strategies for Large Language Models: Tensor Parallelism 101
Multi-GPU Inference Strategies for Large Language Models: Tensor Parallelism 101

Tamara Weed, Dec, 17 2025

Tensor parallelism is the key technique for running large language models across multiple GPUs. Learn how it splits model layers to fit bigger models on smaller hardware, its real-world performance, and how to use it with modern frameworks.

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Science & Research

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tensor parallelism multi-GPU inference LLM deployment model parallelism GPU optimization

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