Why GLM-4.6 is the New King of Autonomous Agents (Sorry, Claude)

While everyone was watching OpenAI and Anthropic, Zhipu AI quietly released GLM-4.6, and it is a monster for agentic workflows.

If you are building autonomous agents that need to use tools (like searching the web, running code, or querying databases), you need to pay attention.

What is GLM-4.6?

Released in late 2025, GLM-4.6 is an open-weight model with a massive 200k context window and a specific architecture designed for Tool Use.

Unlike other models where "function calling" feels like an afterthought, GLM-4.6 treats external tools as native extensions of its brain.

The Benchmark: "The Travel Agent Test"

We devised a complex test to see how well the models could handle a real-world agent task.

The Prompt:

"Find me a flight from NY to London for under $600 next Tuesday, then find a hotel near the airport with a gym, and draft an itinerary email to my boss."

This requires:

1. Tool 1: Flight Search API
2. Tool 2: Hotel Search API
3. reasoning: Filtering results based on constraints (price, location, amenities)
4. Generation: Writing the email

Claude 3.5 Sonnet Performance

• Result: Success.
• Steps: It called the flight tool, got results. Then called the hotel tool. Then wrote the email.
• Issues: It initially tried to call both tools at once (parallel calling), which is good, but failed to pass the date from the flight to the hotel search correctly. It needed a self-correction step.

GLM-4.6 Performance

• Result: Flawless Success.
• Steps: It understood the dependency immediately. It searched for the flight first to confirm the arrival date (since a flight might land the next day), then used that correct date for the hotel search.
• The "Aha!" Moment: This subtle reasoning—realizing that "next Tuesday flight" might mean a "Wednesday hotel check-in"—is what separates a script from an Agent.

Why GLM-4.6 Wins on "Agentic Feel"

1. Structured Output consistency

GLM-4.6 follows JSON schemas for tool calls with near 100% accuracy. We threw nested, complex JSON structures at it, and it didn't hallucinate a single field.

2. Cost

It is significantly cheaper than Claude 3.5 Sonnet (approx 10x cheaper per token). For an agent that might run in a loop 100 times to solve a coding bug, this cost difference is the difference between a viable product and a bankruptcy.

3. Open Weights

You can host GLM-4.6 yourself. For enterprise agents dealing with sensitive data (PII, healthcare), this is a non-negotiable feature that Claude cannot match.

How to use GLM-4.6 today

It is not yet integrated into Cursor by default, but you can use it via:

1. OpenRouter: Select zhipu/glm-4.6 in your API settings.
2. Local Hosting: If you have the GPU VRAM (it's a big model, ~355B params), you can run the quantized version.

Conclusion

Claude 3.5 Sonnet is still better at writing creative poetry or explaining philosophy. But if you are building a worker agent—one that needs to execute strict logic, handle tools, and obey schemas—GLM-4.6 is the new state of the art.

Check out our GLM-4.6 Agent Templates →