Overview
In the rapidly evolving landscape of AI-assisted software development, developers are constantly seeking the most reliable model to handle complex programming tasks. In this PeerLM evaluation, we conducted a head-to-head comparison of OpenAI: GPT-4o vs Anthropic: Claude Sonnet 4.5, specifically focusing on Coding Performance with 10 Evaluators. By utilizing a rigorous comparative ranking methodology, we assessed how these models handle real-world coding challenges, instruction adherence, and overall accuracy.
Benchmark Results
Our evaluation suite focused on two primary criteria: Accuracy and Instruction Following. The results reveal a clear distinction in performance between the two industry-leading models.
| Rank | Model | Overall Score | Accuracy | Instruction Following |
|---|---|---|---|---|
| 1 | Anthropic: Claude Sonnet 4.5 | 8.42 | 8.42 | 8.42 |
| 2 | OpenAI: GPT-4o | 1.58 | 1.58 | 1.58 |
Criteria Breakdown
The evaluation was centered on two critical pillars for coding tasks:
- Accuracy: The ability of the model to produce syntactically correct, bug-free, and logically sound code snippets based on provided prompts.
- Instruction Following: The capacity to adhere to specific formatting requirements, architectural constraints, and stylistic preferences requested by the evaluators.
Anthropic: Claude Sonnet 4.5 demonstrated a significant lead in both categories, securing an overall score of 8.42. This suggests that for complex coding workflows, Claude Sonnet 4.5 is currently more aligned with the expectations of highly technical evaluators compared to GPT-4o.
Cost & Latency
Understanding the economic and performance trade-offs is essential for scaling AI-driven coding agents. Below is the breakdown of the resource utilization observed during this benchmark run.
| Model | Total Cost (USD) | Avg Prompt Tokens | Avg Completion Tokens | Cost per Output Token |
|---|---|---|---|---|
| Anthropic: Claude Sonnet 4.5 | 0.014019 | 237 | 186 | 0.018817 |
| OpenAI: GPT-4o | 0.006211 | 216 | 101 | 0.015336 |
While OpenAI: GPT-4o offers a more budget-friendly profile, the performance gap in coding accuracy indicates that Anthropic: Claude Sonnet 4.5 provides a higher quality of output per request, which may reduce the need for iterative debugging.
Use Cases
Given the results of this Coding Performance with 10 Evaluators suite, we recommend the following use cases:
- Anthropic: Claude Sonnet 4.5: Best suited for complex software architecture, refactoring legacy code, and tasks where high-precision instruction adherence is critical.
- OpenAI: GPT-4o: Better suited for high-volume, lower-complexity tasks where cost-efficiency and quick iteration are prioritized over maximum logic depth.
Verdict
When comparing OpenAI: GPT-4o vs Anthropic: Claude Sonnet 4.5 for coding tasks, Anthropic: Claude Sonnet 4.5 emerges as the clear leader. With a dominant score of 8.42, it consistently outperformed GPT-4o in both accuracy and instruction following. Developers who prioritize code quality and adherence to complex logic will find Claude Sonnet 4.5 to be the superior choice for their development pipeline.