Overview
In the rapidly evolving landscape of large language models, selecting the right tool for software development is critical. This comparison focuses on OpenAI: GPT-5.4 vs Z.ai: GLM 5, specifically evaluating their Coding Performance with 10 Evaluators. By utilizing PeerLM's rigorous comparative benchmarking, we provide an objective look at how these models perform when tasked with generating, debugging, and refining technical code.
Benchmark Results
The evaluation was conducted using a comparative, ranking-based methodology. Over a series of 10 expert-led assessments, the models were judged on their ability to provide accurate, functional, and instruction-compliant code. The results highlight a clear distinction in model behavior and capability.
| Model | Overall Score | Accuracy | Instruction Following |
|---|---|---|---|
| OpenAI: GPT-5.4 | 6.41 | 6.41 | 6.41 |
| Z.ai: GLM 5 | 3.59 | 3.59 | 3.59 |
Criteria Breakdown
The primary metrics for this run were Accuracy and Instruction Following. OpenAI: GPT-5.4 demonstrated superior consistency, securing an overall score of 6.41. Its ability to adhere to complex coding constraints and provide bug-free logic makes it a formidable tool for production environments. Z.ai: GLM 5, while capable, achieved an overall score of 3.59. It showed a tendency to generate more verbose completions, which may account for its different performance profile in this specific coding suite.
Cost & Latency
Performance is only one piece of the puzzle; understanding the operational cost and speed is essential for integration. The following table breaks down the economic and efficiency metrics observed during the 10-evaluator run.
| Model | Avg Latency (ms) | Total Cost (USD) | Avg Completion Tokens |
|---|---|---|---|
| OpenAI: GPT-5.4 | 0 | $0.010055 | 132 |
| Z.ai: GLM 5 | 570 | $0.009623 | 976 |
While OpenAI: GPT-5.4 operates with a high degree of precision, Z.ai: GLM 5 offers a different trade-off. GLM 5 produces significantly more tokens per response (averaging 976 completions), which may be useful for documentation-heavy workflows, though it incurs a latency cost of 570ms.
Use Cases
- OpenAI: GPT-5.4: Best suited for enterprise-grade software engineering, complex system architecture, and tasks requiring high precision where code correctness is the priority.
- Z.ai: GLM 5: Better suited for scenarios requiring verbose explanations or iterative drafting where the user may prefer a larger output volume at a lower cost per token.
Verdict
When comparing OpenAI: GPT-5.4 vs Z.ai: GLM 5, the data points to a distinct leader in coding efficacy. OpenAI: GPT-5.4 consistently outperforms in accuracy and instruction adherence, making it the preferred choice for developers who cannot compromise on code quality.