Claude Opus 4.5 currently leads in coding benchmarks like SWE-bench Verified, while GPT 5.2 delivers stronger abstract reasoning and math performance on benchmarks like ARC-AGI-2 and AIME.
For developers focused on real-world code tasks, Opus 4.5’s higher SWE-bench accuracy makes it appealing, but GPT-5.2’s broader reasoning strength and professional knowledge performance make it equally competitive in many workflows.
If you want to use both Claude Opus 4.5 and ChatGPT 5.2 without paying double the high subscription fees, consider Global GPT. As an all-in-one AI platform, it allows you to access over 100 of the latest top-tier models at the lowest possible cost. More importantly, it runs very reliably, efficiently supporting both your work and study.
Model Overview — What Are GPT 5.2 and Claude Opus 4.5?
GPT 5.2 is OpenAI’s latest flagship large language model released in December 2025, designed to improve multi-step reasoning, long-context comprehension, and professional knowledge capabilities.
Claude Opus 4.5 is Anthropic’s newest frontier model, focused on enterprise coding quality, autonomous task performance, and safety features. It is widely marketed as a top contender for AI-assisted development.
Both models aim to support coding, reasoning, and general productivity, but their strengths diverge depending on the task type and evaluation criteria.
Side-by-Side Benchmark Comparison
Here’s a direct comparison of key performance metrics from vendor-reported benchmark data:
| Benchmark | GPT-5.2 Thinking | GPT-5.2 Pro | Claude Opus 4.5 |
| SWE-bench Verified (coding) | 80.00% | — | 80.90% |
| GPQA Diamond (science) | 92.40% | 93.20% | ~88% |
| AIME 2025 (math, no tools) | 100% | 100% | ~94% |
| ARC-AGI-2 (abstract reasoning) | 52.90% | 54.20% | 37.60% |
| Humanity’s Last Exam | 34.50% | 36.60% | ~26% |
| FrontierMath Tier 1-3 | 40.30% | — | — |
Key takeaway:
- GPT 5.2 shows especially strong reasoning and math performance on ARC-AGI-2 and AIME benchmarks.
- Claude Opus 4.5 edges ahead in SWE-bench Verified, a rigorous coding benchmark.
Coding Abilities — Real-World Software Engineering
Claude Opus 4.5 recently became the first model to break 80% accuracy on the SWE-bench Verified benchmark, a widely cited test that uses real GitHub issues for coding evaluation. This places it slightly ahead of GPT-5.2.
| Model | SWE-bench Verified (%) |
| Claude Opus 4.5 | 80.90% |
| GPT-5.2 | 80.00% |
While the difference is slight, Opus 4.5’s position at the top of SWE-bench suggests developers can expect strong performance in real-world code fixing and debugging tasks.
Independent community evaluations also report Opus 4.5 narrowly reclaiming first place over other frontier models with the number of 74.4%, although the margin can be small and cost efficiency varies with step settings.
Abstract Reasoning & Mathematical Problem Solving
GPT 5.2 outperforms Claude Opus 4.5 on abstract reasoning benchmarks:
- ARC-AGI-2: GPT 5.2 scores ~52.9–54.2% vs Opus’s ~37.6%
- AIME 2025 (math): GPT 5.2 achieves 100% (no tools) vs ~92.8% for Opus
These metrics indicate that GPT 5.2 has higher aptitude for complex reasoning and novel problem solving, a key factor in research, academic tasks, and logic-intensive workflows.
Writing, General Knowledge & Professional Tasks
OpenAI claims GPT 5.2 achieves strong performance on “knowledge work tasks” across 44 occupations with its internal GDPval evaluation, reportedly beating or tying industry professionals 70.9% of the time at much lower cost. However, this benchmark is proprietary and not independently validated.
Independent public benchmarks are limited in measuring these domains, but the existing data suggest GPT 5.2’s broad reasoning capabilities translate well beyond code into writing, research, and professional workflows.
Pricing, Token Costs & Value for Developers
Pricing varies by API and subscription plan, but public data show:
- Claude Opus 4.5: ~$5 per million input tokens and ~$25 per million output tokens (significant reduction from prior versions)
- OpenAI GPT models: You can choose to subscribe to different plans, or use the API. The api price for the Thinking and Instant versions is slightly higher than GPT 5.1, at $1.75 per million input tokens. In addition, the Pro API version costs up to $21 per million tokens, which is quite unaffordable. If you want to save on costs, consider Global GPT, which offers the same performance as the official models but at prices as low as 30% of the official rates.
Developer Experience & Ecosystem Integration
Both models integrate into popular development workflows:
- GPT 5.2 benefits from the extensive ChatGPT ecosystem, deep tooling, and IDE plugins supported by OpenAI’s broad adoption.
- Claude Opus 4.5 offers advanced “effort” parameters and agentic capabilities designed for autonomous code execution and debugging workflows.
Which Model Should You Choose? — Use-Case Recommendations
Choose GPT 5.2 if:
✔ Need strong abstract reasoning & math performance
✔ You prioritize general knowledge tasks
✔ You want broader ecosystem support and tool integration
Choose Claude Opus 4.5 if:
✔ You need the best coding accuracy on real-world code tasks
✔ You value autonomous, agent-style code execution
✔ Enterprise workflows requiring sustained, high-quality debug suggestions
Conclusions — Who Wins the AI Face-Off?
There is no definitive “winner” across all tasks:
- Claude Opus 4.5 leads in coding accuracy on SWE-bench, making it a strong choice for developers.
- GPT 5.2 excels in reasoning, math, and broad professional tasks, giving it an edge in research and multifaceted workflows.
Both models push the state of the art in 2025 AI capabilities — your choice should match your primary needs.
FAQ — Quick Answers for Common Queries
Is GPT5.2 better than Claude Opus4.5 at coding?
Not strictly — Opus 4.5 achieves slightly higher SWE-bench Verified scores.
Which is cheaper for bulk APIusage?
It depends on the tier. The API price for GPT 5.2 Pro is more than four times that of Claude Opus.
Which is better for abstract reasoning?
GPT 5.2 generally outperforms in reasoning benchmarks like ARC-AGI-2.
