OpenClaw — the open-source personal AI agent with 333K+ GitHub stars — now officially supports GLM-5.1. This combination pairs OpenClaw's always-on agent architecture with GLM-5.1's long-horizon agentic capabilities. Here's how to set it up, configure it for optimal performance, and build skills that leverage GLM-5.1's sustained optimization abilities.

1Why GLM-5.1 + OpenClaw?

OpenClaw runs as an always-on agent that connects to your messaging apps, takes real-world actions, and executes multi-step workflows. GLM-5.1's long-horizon capabilities — sustained productivity over hundreds of iterations and thousands of tool calls — make it an ideal backbone for OpenClaw's skill system. Where other models plateau after initial gains, GLM-5.1 keeps improving.

Key advantages of this pairing:

• Extended task execution — GLM-5.1 stays productive over long OpenClaw skill runs
• Strong coding capabilities — SWE-Bench Pro 58.4% for code-related skills
• MIT License — no restrictions on how you use it within OpenClaw
• Cost-effective — self-host for unlimited usage or use the Coding Plan with promotional rates

2Prerequisites

• OpenClaw installed (npm install -g openclaw)
• A GLM Coding Plan subscription from z.ai/subscribe, or a self-hosted GLM-5.1 instance
• Your Z.ai API key from the Coding Plan dashboard

3Configuration via Onboarding Wizard

The fastest path:

When prompted for your LLM provider, select "Custom / OpenAI-compatible" and enter:

• API Base URL: https://api.z.ai/v1
• API Key: your GLM Coding Plan key
• Model: GLM-5.1

4Manual Configuration

If you prefer manual setup, edit your OpenClaw configuration:

5Optimizing GLM-5.1 Settings for OpenClaw

To get the most out of GLM-5.1 within OpenClaw:

• Set temperature: 1.0 and top_p: 0.95 to match benchmark-optimal settings
• Use max_tokens: 32768 for complex skill outputs
• Enable think mode for skills requiring multi-step reasoning
• Set generous timeout values — GLM-5.1 improves with more time

6Building Skills with Long-Horizon Capabilities

GLM-5.1's sustained optimization capabilities are particularly valuable for OpenClaw skills that involve:

• Code generation skills — generate entire repositories or complex features with iterative refinement
• Optimization skills — performance tuning, cost optimization, infrastructure right-sizing
• Research skills — deep web research with iterative query refinement
• Content creation skills — long-form content with self-review and polish cycles

Design your SOUL.md to encourage iterative self-review — GLM-5.1 excels when given the opportunity to evaluate and improve its own output.

7Multi-Agent Routing with GLM-5.1

OpenClaw supports multiple agents with different model configurations. A powerful pattern: use GLM-5.1 for coding and optimization agents (where long-horizon capabilities matter most) and a smaller, faster model for quick conversational agents. Configure routing rules in your AGENTS.md to direct tasks to the appropriate model.

8Cost Management Tips

• Schedule heavy workloads during off-peak hours (outside 14:00–18:00 UTC+8) for 2× quota rate
• Take advantage of the promotional 1× off-peak rate through April 2026
• For high-volume usage, self-host GLM-5.1 to eliminate per-token costs
• Use multi-agent routing to reserve GLM-5.1 for tasks that benefit from its capabilities

9Troubleshooting Common Issues

10Lushbinary OpenClaw Deployment

At Lushbinary, we specialize in deploying and customizing OpenClaw with frontier AI models. From initial setup to custom skill development and production scaling, we can help you build powerful AI agent workflows with GLM-5.1.

❓ Frequently Asked Questions

📚 Sources

• Z.ai — GLM-5.1: Towards Long-Horizon Tasks (April 7, 2026)
• HuggingFace — GLM-5.1 Model Weights
• GitHub — GLM-5.1 Repository

Content was rephrased for compliance with licensing restrictions. Benchmark data sourced from official Zhipu AI publications as of April 8, 2026. Pricing and availability may change — always verify on the vendor's website.