Infrastructure

The AI hardware landscape has shifted significantly in 2026, with NVIDIA, AMD, and Intel all competing for developers who need GPUs capable of running local large language models and AI inference workloads.

Australia has RTX 5090 stock. Barely. And if you find one, you will pay a premium that feels detached from reality.

A hub for compute hardware analysis covering GPUs, CPUs, memory trends, and AI-focused workstation infrastructure.

Production AI systems depend on far more than models and prompts.

Strategic guide to hosting large language models locally with Ollama, llama.cpp, vLLM, or in the cloud. Compare tools, performance trade-offs, and cost considerations.

A performance engineering hub for running LLMs efficiently: runtime behavior, bottlenecks, benchmarks, and the real constraints that shape throughput and latency.

In the midst of the modern world’s turmoil here I’m comparing tech specs of different cards suitable for AI tasks (Deep Learning, Object Detection and LLMs). They are all incredibly expensive though.