Promptfoo vs lm-eval-harness: when each is useful
A practical comparison of two popular evaluation tools — one for product regression testing, one for benchmark reproduction — and when to reach for each.
Comparisons
Models, tools, hosts — compared honestly
Side-by-side comparisons of models, evaluation tools, hosting platforms, and infrastructure choices. No marketing league tables — just the practical differences that change your cost, latency, control, and switching risk.
6published comparisons
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Live comparisons
Model gateways and routers: OpenRouter, LiteLLM and build-vs-buy
A practical comparison of model gateway options: when to use OpenRouter for quick multi-provider access, LiteLLM for self-hosted routing, and when building your own makes sense.
Cloud AI platforms vs direct model APIs: Bedrock, Vertex and Azure trade-offs
Cloud AI platforms offer governance and consolidated billing but add abstraction layers and lock-in risk. How to decide between cloud AI and direct provider APIs.
Hosted API vs self-hosted open model: the real cost comparison
A practical cost comparison between using hosted LLM APIs and running open models on your own infrastructure, including utilisation, ops labour, scaling, latency and failure handling.
GPU rental for LLM inference: what an operator needs to know
How caching and batching change the math on GPU rental costs, and when renting beats — or loses to — API calls for open model inference.
Fine-tuning economics: when training a custom model pays back
A cost comparison of fine-tuning versus prompting and RAG — what drives the break-even point, when it makes financial sense, and the hidden costs teams miss.
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