Overview
In the rapidly evolving landscape of Large Language Models, choosing the right architecture for software development tasks is critical. This PeerLM evaluation focuses on Coding Performance with 10 Evaluators, pitting the industry-leading OpenAI: GPT-5.4 against the specialized MiniMax: MiniMax M2.5. By utilizing a comparative ranking methodology, we provide an objective look at how these models handle complex coding prompts and instruction-following requirements.
Benchmark Results
The evaluation was conducted across a standardized set of coding prompts. OpenAI: GPT-5.4 secured the top rank, demonstrating superior capability in both accuracy and adherence to specific coding constraints.
| Model | Overall Score | Accuracy | Instruction Following |
|---|---|---|---|
| OpenAI: GPT-5.4 | 6.49 | 6.49 | 6.49 |
| MiniMax: MiniMax M2.5 | 3.51 | 3.51 | 3.51 |
Criteria Breakdown
Our evaluators assessed models based on two core pillars: Accuracy and Instruction Following. The score spread between the two models is 2.98, indicating a significant performance gap in the current testing environment.
- Accuracy: OpenAI: GPT-5.4 consistently provided more syntactically correct and logically sound code blocks compared to MiniMax: MiniMax M2.5.
- Instruction Following: When faced with multi-step coding constraints (e.g., specific library requirements or formatting styles), OpenAI: GPT-5.4 maintained a higher level of fidelity to the prompt instructions.
Cost & Latency
Efficiency is a vital consideration for production-grade applications. While OpenAI: GPT-5.4 leads in performance, users should weigh this against the cost per token and latency metrics.
| Model | Avg Latency (ms) | Cost Per Output Token |
|---|---|---|
| OpenAI: GPT-5.4 | N/A | $0.01908 |
| MiniMax: MiniMax M2.5 | 870ms | $0.001281 |
Use Cases
OpenAI: GPT-5.4 is best suited for complex architectural tasks, legacy code refactoring, and scenarios where the cost of debugging incorrect code outweighs the higher inference price. Its robust performance makes it the gold standard for high-stakes development.
MiniMax: MiniMax M2.5 excels in high-volume, cost-sensitive environments. With a significantly lower cost per output token, it is an attractive option for simple script generation, boilerplate code creation, or rapid prototyping where iterative feedback loops are permitted.
Verdict
OpenAI: GPT-5.4 is the clear leader in this evaluation, offering superior coding precision and instruction adherence. While MiniMax: MiniMax M2.5 provides a more budget-friendly alternative, it currently trails in overall performance metrics. Developers must choose between the high-fidelity output of GPT-5.4 or the cost-effective efficiency of MiniMax M2.5 based on their specific project requirements.