GLM-5 is absolutely incredible for coding (7 new features)

Woah this is huge.

China's Z.ai just released their brand new GLM-5 model and it's absolutely incredible. I hope Windsurf adds support for this ASAP...

This is not just a "coding" model. This is full-blown software engineering.

They designed it from the ground up to build highly complex systems and intricate dev workflows.

Record-low hallucinations -- from 90% in the previous version... to 34% in GLM-5. Thanks to a groundbreaking approach to training the model.

Like for example if I ask the model a question it doesn't know -- it's more likely to just tell me it doesn't know -- instead of inventing garbage on the fly -- like I see at times from GPT and the rest.

And it's open-source with open weights (!)

Let's check all the amazing features in this release.

1. Agent-first behavior (designed to stay on task)

GLM-5 is positioned around what developers call agent workflows — situations where the model has to plan, execute, check results, and continue working toward a goal instead of responding once and stopping.

The main improvement here isn’t personality or creativity. It’s consistency. The model is tuned to maintain context and direction over longer sequences of actions, which is essential if you want AI to handle real workflows instead of isolated prompts.

2. A true coding-focused model

Software engineering is one the first and foremost priorities of this new model.

GLM-5 is optimized for working across larger codebases and longer development tasks rather than generating small snippets.

In practice this means keeping track of project structure, following constraints across files, and iterating toward working solutions. Improvements in coding usually signal broader gains in reasoning and planning — since programming requires precision and structured thinking.

3. Very large context window (so it can hold more of the problem at once)

GLM-5 supports extremely long context lengths, allowing large amounts of text, documentation, or code to stay visible to the model at once.

This matters more than it sounds. Instead of feeding information piece by piece, developers can provide entire specifications or large repositories in one session. That reduces fragmentation and makes long-running tasks far more stable.