# 第十四章 性能与成本优化实战

本章从 Token 消耗、推理延迟、用量观测与预算治理四个维度，提供基于 OpenClaw 内置观测能力、provider 限额和外部治理机制的系统化优化方案，帮助在保持服务质量的前提下有效降低运行成本。

## 本章内容导读

本章包括以下几个小节，从 Token 消耗、形式化延迟与成本模型、实时预算控制、到规模化部署模板，提供系统化的性能与成本优化方案：

* [**14.1 Token 与上下文成本**](/openclaw_guide/di-si-bu-fen-shi-zhan-yu-you-hua-shen-du-zhi-nan/14_performance_cost/14.1_token_context_cost.md)：Token 流向分析、系统提示精简、上下文压缩策略（Compaction 与 Pruning）、模型分层选择。
* [**14.2 延迟与吞吐优化**](/openclaw_guide/di-si-bu-fen-shi-zhan-yu-you-hua-shen-du-zhi-nan/14_performance_cost/14.2_latency_throughput.md)：形式化延迟模型分解（LLM + 工具 + 沙箱 + 编排），多智能体场景的延迟累积，结构化成本模型。
* [**14.3 OpenClaw 的用量观测与预算控制**](/openclaw_guide/di-si-bu-fen-shi-zhan-yu-you-hua-shen-du-zhi-nan/14_performance_cost/14.3_usage_budget.md)：内置用量命令（`/status`、`/usage cost`、`/compact`）、Dashboard Usage 视图，以及 provider 限额、外部监控或插件治理。
* [**14.4 不同规模部署预算模板**](/openclaw_guide/di-si-bu-fen-shi-zhan-yu-you-hua-shen-du-zhi-nan/14_performance_cost/14.4_budget_templates.md)：个人、中等、企业三种场景的成本要素分解与预算规划模板。
* [**14.5 本章小结**](/openclaw_guide/di-si-bu-fen-shi-zhan-yu-you-hua-shen-du-zhi-nan/14_performance_cost/summary.md)：关键结论与优化检查清单。


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