Open-source AI has been improving rapidly, but for a long time, proprietary models like GPT and Gemini dominated when it came to coding, reasoning, and creative tasks. I decided to test the latest GLM 4.7 to see if it could really compete. The results were surprisingly practical, and in some areas, it even rivaled closed-source alternatives. Here’s what I found.
GLM 4.7 is more than just an update. It brings significant improvements in:
- Coding Performance: Better handling of multilingual coding and terminal-based tasks.
- UI Generation and Design:** Cleaner web pages and slides with accurate layout and sizing.
- Tool Usage and Reasoning: Improved multi-step task handling and web browsing.
- Complex Reasoning: Boosted performance in logical and mathematical tasks.
- In short, GLM 4.7 feels more like a real coding partner than just a language model.
Hands-On Testing Scenarios
To understand its practical value, I tested GLM 4.7 across four different scenarios.
Scenario 1: Multi-step Coding Task
Prompt:
“Write a Python script that reads a CSV file of sales data, calculates total revenue per product, and outputs a sorted list of products by revenue. Include proper comments and exception handling.”
Output :
- Full Python script with comments, exception handling, and aggregation logic.
- Handles invalid data and creates sample CSV data for testing.
Scenario 2: Slide Deck Generation
Prompt:
“Create a 5-slide presentation on AI in healthcare. Include titles, main points, and layout suggestions for each slide.”
Output Highlights:
- Each slide includes title, bullet points, and visual layout suggestions.
- Covers diagnostics, drug discovery, ethics, and future outlook.
- Provides style, icons, and color recommendations for slide design.
Shows GLM 4.7 can assist in practical content creation, saving time for presentations.
Scenario 3: Landing Page Generation
Prompt:
“Generate HTML and CSS for a modern portfolio landing page with a header, about section, and project gallery. Ensure responsive design.”
Output Highlights:
- Generates clean, responsive HTML and CSS.
- Includes header, about section, and project gallery with layout guidance.
- Fully usable as a starting point for a web project.
Value:
Demonstrates GLM 4.7 as a web design assistant, not just a coding tool.
Scenario 4: Creative Writing
Prompt:
“Write a short story (300-400 words) about a robot learning to code alongside humans. Include dialogue and problem-solving moments across three distinct scenes.”
Output :
- Multi-scene story about Seven, a robot learning coding with a human mentor.
- Includes dialogue, problem-solving, and growth over time.
- Shows reasoning and creativity in narrative form.
- Shows GLM 4.7 beyond coding and slides.
- Engages both technical and creative audiences.
- Demonstrates versatility of open-source AI for storytelling or content creation
What This Means for Open-Source AI
GLM 4.7 proves that open-source AI is closing the gap with closed-source models:
It can handle real coding tasks.
It can generate visually structured content like web pages.
It can help in creating slides and structuring them (It cannot generate slides but helps in creation)
It can even produce creative writing with reasoning and narrative structure.
The gap may not be fully closed yet, but the difference is shrinking fast. Developers and creators now have affordable, flexible, and practical AI tools that can be used locally or via APIs.
Try It Yourself
Z.ai API: GLM 4.7 Documentation
Local Deployment: HuggingFace and ModelScope offer model weights.
Coding Agents: Compatible with Claude Code, Roo Code, and Kilo Code.
You can experiment with coding, slide decks, landing pages, or creative writing. Test the prompts in this article, tweak them, and see how GLM 4.7 adapts.
Wrapping Up
Open-source AI is no longer just a curiosity. GLM 4.7 shows it can be a practical, versatile partner for developers, designers, and creators. If you’ve been hesitant about using open-source AI, now is the time to explore.
What do you think? Have you tried GLM 4.7 yet? How does it compare to GPT, Gemini, or other tools you’ve used? Share your experiences in the comments.
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