OpenClaw Performance Optimization Guide OpenClaw 性能优化完全指南
OpenClaw Performance Optimization Guide
Why Optimization Matters
Running an AI agent 24/7 requires careful optimization. Without it, you’ll burn through tokens and experience lag.
5 Key Optimization Techniques
1. Thinking Mode
{
"thinkingDefault": "minimal"
}
- Reduces response time from 2.2s to 1.1s
- Use “minimal” for real-time interactions
2. WebSocket Throttle
# Reduce throttle for faster responses
WebSocket throttle: 150ms → 20ms
# 7x faster voice response!
3. Prompt Caching (v2026.2.0+)
- 90% cost reduction
- Cache common prompts
4. Model Routing
- Use cheap models for heartbeat
- Reserve expensive models for complex tasks
- Example: Haiku → Sonnet → Opus
5. Context Window Management
- Set
contextTokens: 80000limit - Regular compaction
- Reserve 24000 tokens floor
Cost Comparison
| Setup | Monthly Cost |
|---|---|
| Default | $87/month |
| Optimized | $27/month |
| Savings | 70% |
Conclusion
Optimization is essential for production AI agents. Start with these 5 techniques!
OpenClaw 性能优化完全指南
为什么优化重要
24/7 运行 AI agent 需要精心优化。否则你会快速烧光 tokens 并体验延迟。
5 大优化技术
1. 思考模式
{
"thinkingDefault": "minimal"
}
- 响应时间从 2.2s 降到 1.1s
- 实时交互用 “minimal”
2. WebSocket 节流
# 减少节流以获得更快响应
WebSocket 节流: 150ms → 20ms
# 语音响应快 7 倍!
3. Prompt 缓存 (v2026.2.0+)
- 成本降低 90%
- 缓存常用 prompts
4. 模型路由
- heartbeat 用便宜模型
- 复杂任务用贵模型
- 示例: Haiku → Sonnet → Opus
5. 上下文窗口管理
- 设置
contextTokens: 80000限制 - 定期压缩
- 保留 24000 tokens 底线
成本对比
| 配置 | 月成本 |
|---|---|
| 默认 | $87/月 |
| 优化后 | $27/月 |
| 节省 | 70% |
结论
优化对生产级 AI agents 至关重要!从这5个技术开始!