Overview
Choosing the right Large Language Model for software engineering tasks is critical for productivity and codebase integrity. In this report, we analyze the performance of two prominent models: Mistral: Mistral Large 3 2512 and Z.ai: GLM 5. Through our rigorous PeerLM evaluation framework, titled "Coding Performance with 10 Evaluators," we have assessed their ability to handle complex programming tasks, instruction adherence, and overall output accuracy.
Benchmark Results
The comparative evaluation highlights a significant performance gap between the two contenders. Z.ai: GLM 5 has demonstrated superior capability in coding scenarios, securing the top rank in our leaderboard.
| Model | Overall Score | Accuracy | Instruction Following |
|---|---|---|---|
| Z.ai: GLM 5 | 8.46 | 8.46 | 8.46 |
| Mistral: Mistral Large 3 2512 | 1.54 | 1.54 | 1.54 |
Criteria Breakdown
The evaluation focused on two primary pillars of coding proficiency: Accuracy and Instruction Following. By utilizing a comparative ranking method, our 10 evaluators assessed how each model handled code generation, debugging, and logic implementation.
- Accuracy: Z.ai: GLM 5 consistently provided more syntactically correct and logically sound code snippets compared to Mistral: Mistral Large 3 2512.
- Instruction Following: When presented with complex constraints, Z.ai: GLM 5 maintained alignment with the prompt requirements, whereas Mistral: Mistral Large 3 2512 struggled to meet the specific criteria set by the evaluators.
Cost & Latency
Understanding the economic trade-offs is essential for scaling development workflows. While Z.ai: GLM 5 leads in performance, it operates at a different price point than Mistral: Mistral Large 3 2512.
| Model | Total Cost (USD) | Cost per Output Token | Avg Completion Tokens |
|---|---|---|---|
| Z.ai: GLM 5 | $0.009623 | $0.002465 | 976 |
| Mistral: Mistral Large 3 2512 | $0.001428 | $0.002164 | 165 |
Use Cases
The choice between these models depends on your project requirements. Z.ai: GLM 5 is the clear choice for high-stakes coding tasks, such as building complex backend logic, refactoring legacy code, or implementing new features where accuracy is non-negotiable. Conversely, Mistral: Mistral Large 3 2512 may serve as a cost-effective alternative for simpler boilerplate generation or tasks where the developer is performing heavy oversight and quick iteration.
Verdict
When evaluating Mistral: Mistral Large 3 2512 vs Z.ai: GLM 5, the data clearly favors Z.ai: GLM 5 for professional coding applications. With an overall score of 8.46 against 1.54, Z.ai: GLM 5 proves to be the more reliable partner for technical tasks, despite the higher cost profile.