Overview
In the rapidly evolving landscape of large language models, choosing the right tool for programming tasks is critical. This comparison focuses on OpenAI: GPT-5.2 vs Anthropic: Claude Sonnet 4.5, utilizing PeerLM's rigorous evaluation suite, 'Coding Performance with 10 Evaluators.' This benchmark leverages comparative ranking to determine how these models handle real-world coding challenges, specifically focusing on accuracy and the ability to strictly follow complex instructions.
Benchmark Results
The comparative evaluation reveals a clear hierarchy in performance for coding-specific workflows. With a score spread of 1.06 across the criteria, Anthropic: Claude Sonnet 4.5 currently holds the top position in our rankings, demonstrating superior performance in the eyes of our 10 evaluators.
| Model | Overall Score | Accuracy | Instruction Following |
|---|---|---|---|
| Anthropic: Claude Sonnet 4.5 | 5.53 | 5.53 | 5.53 |
| OpenAI: GPT-5.2 | 4.47 | 4.47 | 4.47 |
Criteria Breakdown
Our evaluation criteria were split into two primary pillars: Accuracy and Instruction Following. In the context of software engineering, accuracy measures the correctness of the code generated, while instruction following assesses how well the model adheres to specific constraints, such as library restrictions, stylistic guidelines, or architectural requirements.
- Accuracy: Claude Sonnet 4.5 outperformed GPT-5.2, indicating a higher rate of functional, bug-free code snippets.
- Instruction Following: The 10 evaluators consistently ranked Claude Sonnet 4.5 higher when asked to integrate specific coding patterns or adhere to complex, multi-step prompts.
Cost & Latency
While performance is paramount, economic efficiency is equally important for production-grade applications. Below is the breakdown of cost efficiency for the models evaluated.
| Model | Total Cost (USD) | Cost per Output Token |
|---|---|---|
| Anthropic: Claude Sonnet 4.5 | $0.014019 | $0.018817 |
| OpenAI: GPT-5.2 | $0.010465 | $0.016352 |
OpenAI: GPT-5.2 proves to be the more cost-effective option, offering a lower price point per output token. For high-volume environments where cost management is a priority, GPT-5.2 provides a compelling balance between capability and expenditure.
Use Cases
Anthropic: Claude Sonnet 4.5 is best suited for complex, mission-critical coding tasks where precision and adherence to strict project constraints are non-negotiable. Its higher ranking in this evaluation suggests it handles nuanced, multi-part requirements more reliably.
OpenAI: GPT-5.2 is an excellent choice for rapid prototyping, standard boilerplate generation, and large-scale applications where budget optimization is required. Developers looking for a high-performing model that offers the best value for their token spend will find GPT-5.2 highly advantageous.
Verdict
The comparative analysis of OpenAI: GPT-5.2 vs Anthropic: Claude Sonnet 4.5 highlights a trade-off between peak performance and cost-efficiency. If your project demands the highest level of accuracy and instruction compliance, Anthropic: Claude Sonnet 4.5 is the clear winner. However, for teams optimizing for cost without sacrificing significant capability, OpenAI: GPT-5.2 remains a formidable and efficient alternative.