OpenClaw Performance: Optimizing Your Self-Hosted AI
Your OpenClaw agent's performance depends on three things: the AI model you choose, the server it runs on, and how the Gateway is configured. Here's how to optimize each one for the fastest, most cost-effective experience.
OpenClaw Performance Factor 1: Model Selection
The single biggest impact on response speed and cost is your AI model choice. Here's how the supported models compare:
| Model | Speed | Quality | Cost |
|---|---|---|---|
| Claude Haiku 4.5 | Very fast | Good | Very low |
| GPT-5 Mini | Very fast | Good | Very low |
| Gemini 3 Flash | Fast | Good | Low |
| Claude Sonnet 4.5 | Moderate | Very good | Moderate |
| Gemini 3 Pro | Moderate | Very good | Moderate |
| GPT-5.2 | Moderate | Excellent | Higher |
| Claude Opus 4.6 | Slower | Excellent | Highest |
Performance tip: Use Claude Haiku 4.5 or GPT-5 Mini as your default model for everyday tasks. They respond in under a second and handle most requests well. Switch to a premium model only when you need deep reasoning, complex analysis, or creative writing.
OpenClaw Performance Factor 2: Server Sizing
OpenClaw itself is lightweight — the Gateway, channel adapters, and skills system don't need much compute. Most of the "heavy lifting" happens on the AI provider's servers. But server size still matters for:
- Concurrent sessions. More users chatting simultaneously means more sessions to manage.
- Skill execution. Skills that browse the web, process files, or run shell commands benefit from more CPU and RAM.
- Media handling. Processing images, audio, and documents requires more resources.
Recommended Server Sizes
- Small (2 vCPU / 4 GB) — Perfect for a single user or small team with standard chat workflows.
- Medium (4 vCPU / 8 GB) — Good for heavier usage, multiple channels, or media-heavy workflows.
- Large (8 vCPU / 16 GB) — For power users running many skills, processing large documents, or serving multiple team members.
- Extra Large (16 vCPU / 32 GB) — For enterprise deployments with high concurrency and resource-intensive operations.
OpenClaw Performance Factor 3: Network and Location
The response latency you experience is the sum of:
- Message from your chat app to the Gateway (~50–200ms).
- Gateway processing and skill execution (~10–100ms).
- API call to the AI model provider (~500–5000ms depending on model).
- Response back through the same path (~50–200ms).
The AI model API call dominates total latency. To minimize it:
- Choose a server location close to your AI provider's data centers. European servers (Hetzner) work well with Anthropic and Google's EU endpoints.
- Use faster models (Haiku, GPT-5 Mini, Gemini Flash) for time-sensitive interactions.
- Keep prompts concise. Longer prompts take longer to process.
OpenClaw Performance Tips
- Keep OpenClaw updated. Performance improvements ship regularly. Run the latest version.
- Disable unused skills. Every loaded skill adds a small amount of overhead. Only enable what you use.
- Monitor resource usage. The OneClickClaw dashboard shows uptime, CPU, and memory usage. Scale up before you hit limits.
- Use model routing. The community ClawRouter automatically selects fast models for simple queries, saving both time and money.
- Restart periodically. The OpenClaw daemon handles this automatically, but a fresh Gateway process is always snappiest.
OpenClaw Performance on OneClickClaw
When deployed through OneClickClaw, your OpenClaw instance runs on Hetzner's infrastructure with SSD storage, dedicated vCPUs, and low-latency network connections. The provisioning process optimizes the server configuration for OpenClaw specifically — Node.js tuning, firewall rules, and daemon configuration are all handled automatically.
Start with the Small plan. If you find you need more performance, upgrade to Medium or Large through the dashboard with zero downtime.