AI Models Battle: GLM-4.7, Opus 4.5, GPT-5.2

In the ever-evolving landscape of AI, the recent showdown between GLM-4.7, Opus 4.5, and GPT-5.2 is like a tech version of the Fast & Furious saga. Each model's performance in building an F1 dashboard was put to the test, and let's just say, the results were as varied as a season of plot twists in a reality show.

The Setup: One Shot, No Edits

The video from Snapper AI sets the stage for a controlled, one-shot AI coding benchmark. Each model received the same Product Requirements Document (PRD) for an F1 dashboard, and was tasked with a single prompt—no follow-ups or human edits allowed. This test wasn’t about who could build the flashiest dashboard, but rather, how each model behaves under identical constraints.

"This isn’t about absolute capability. It’s about model behavior under constraints, and what that means for real-world AI coding workflows," the video notes.

The Scoreboard: Different Models, Different Strengths

After the dust settled, the scoreboard revealed Opus 4.5 and GPT-5.2 leading the pack, while GLM-4.7 struggled a bit like an underdog in a superhero movie. But it's not just about the numbers.

• GLM-4.7: Scored an average of 66. It was praised for architectural intent but fell short in data integrity and runtime stability.
• Opus 4.5: Averaged an 83, scoring high on structure and UI design, but knocked down for data integrity violations by GPT's stricter review.
• GPT-5.2: Topped the charts with a 91, thanks to its focus on data correctness and release safety, despite some minor lint issues.

The Tech Stack Tango

Each model chose its own tech stack, with Opus opting for a V-based client-only React app, while GPT and GLM went for a Nex.js setup. These choices weren't about right or wrong but highlighted how stack decisions influence model performance.

"None of these choices are right or wrong. They just come with different trade-offs," the video explains.

Review Philosophies: The Critical Eye vs. The Design Guru

The divergence in scores also stems from how each model reviewed the builds. Opus tends to reward architectural completeness, treating most issues as fixable. GPT, on the other hand, is like that tough professor who won’t let anything slide when it comes to data integrity.

"Opus tends to reward architectural completeness and overall structure. GPT 5.2 is far stricter on data integrity," the video points out.

The Cost of Speed

In terms of build times, GPT 5.2 was the fastest, wrapping up in just over 23 minutes, while GLM-4.7 took double that time. But here's the kicker: faster doesn't always mean better. The cost-effectiveness of each model depends on your specific needs, whether it's rapid iterations or ensuring data correctness.

So, Which One Fits Your Workflow?

The takeaway isn’t about crowning a singular winner. Each model brings something unique to the table. If you're about that life of structure and visual flair, Opus is your go-to. Need bulletproof data integrity? GPT's got your back. And if speed and iterations are your jam, GLM might just be the underdog you root for.

Remember, this battle was just one snapshot. In different environments or with iterative prompts, these models could perform very differently. So, what's your move? Let the workflow composition guide your choice.

By Tyler Nakamura, your go-to guy for making sense of the tech world one gadget at a time.