The economics of agents are decided on the input side, not the output side, so cache discounts now shape which models are viable for long-running workflows. Builders choosing between Anthropic and Google DeepMind for agent deployments can use the session data to estimate real token spend before committing. The caching walkthrough with live sessions doubles as a practical cost-optimisation reference.
Threads cut upload overhead and latency for long-running agents, but they are not a cost-saving feature: billable tokens are identical and caching still has to be configured separately. Developers building computer-use or document-heavy agents benefit most, since screenshots and files no longer need re-uploading every turn. Teams with strict data retention or HIPAA requirements should hold off, and batch processing is not yet supported.
The non-obvious takeaway is that caching bugs produce no errors at all — teams simply pay more per token while assuming caching works. Platform and backend engineers running agent workloads on OpenAI, Anthropic or other provider APIs can run CACHELINT on their own repos before costs accumulate. As an academic tool study with no pricing or regional availability angle, its closest comparison is other static-analysis approaches like CodeQL-based linting, which CACHELINT extends with provider-aware precondition checks.
Claude Code 新增空闲压缩，缓存过期前自动帮你 compact，隔一小时回来继续用能省不少 token 费，不想用可在 settings.json 里关掉。
SambaNova给MiniMax M3加了缓存功能，还分享了SN50的ROI数据，想知道AI基建圈最新动态的可以看看。
OpenAI 给 GPT-6 的 API 上线了更好的提示词缓存，默认命中率更高，缓存输入最高打一折，跑智能体的成本和延迟都能降下来。
OpenAI 出了个提示词缓存的调优教程，教你设 cache breakpoints、调 reasoning effort 还不丢缓存，做应用的开发者可以直接抄作业。
OpenAI 把 GPT-6 Astra 的能力塞进了更便宜更快的 Sol 和 Luna，缓存读取打 1 折，API 价格比 GPT-5.6 还低一半。
装了之后敲一下 /cache-stats，缓存命中率和 token 成本一目了然，调提示词时省事多了。
