RecommendDay is an independent bilingual editorial site about AI models, AI tools, solution cost, frontier changes, and the infrastructure needed to run real products rather than demos.
The guiding idea is simple: useful AI should travel further, but recommendation without measurement is not help. A good guide should say what changed, who benefits, what it costs, where it can fail, and what the reader should verify before committing.
What we publish
- Model and provider selection notes for teams deciding between frontier APIs, open-weight models, hosted tools, and hybrid stacks.
- Cost breakdowns that separate token pricing, inference latency, context length, storage, evaluation, human review, and infrastructure.
- Source-led explainers for AI claims that are easy to misunderstand: benchmark scores, preview labels, context windows, tool use, retrieval, and data controls.
- Infrastructure guides when hosting, backups, observability, or security directly affect AI product cost and reliability.
How to contact
Corrections, vendor context, and source suggestions can be sent to [email protected]. We prefer specific evidence over broad claims.