Articles & research papers
In-depth downloadable articles on AI infrastructure economics, GPU pricing, vendor lock-in and compute strategy.
The GPU Price Is The Wrong Number
This RaisePath insight examines why headline GPU pricing is becoming an increasingly poor measure of the real economics of AI compute. It explores the widening gap between GPU-hour cost and the cost of producing useful AI output, drawing on current H100, H200 and Blackwell pricing, spot-market economics, utilisation, memory capacity, inference performance and model-routing costs. The paper shows how newer or apparently more expensive infrastructure can deliver materially better economics once throughput, cost per token and workload efficiency are taken into account. It also examines the impact of agentic AI, where a single user interaction can trigger multiple model calls and rapidly amplify inference consumption. The central conclusion is that organisations should move beyond comparing GPU rate cards and instead measure cost per useful unit of intelligence. As AI workloads scale, utilisation, workload placement, model choice, caching, context size and infrastructure flexibility will increasingly determine commercial performance.
Article 50 Has a Compute Bill. Europe Is About to Find Out How Big It Is.
Article 50 has quietly changed the economics of AI in Europe. Every machine-readable mark, provenance check and compliance layer has to live somewhere in the stack. At scale, that means more compute, more cost and more pressure on inference infrastructure that is already being pushed hard. We’ve pulled the numbers together, including model pricing, energy demand, EU compute thresholds and the potential cost exposure. If you’re involved in AI infrastructure, cloud, GPUs, procurement or enterprise AI strategy, this is worth a read.
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