Claude 4.1 Opus (Reasoning) vs GPT-5.2 (xhigh)
Comparing 2 AI models · 5 benchmarks · Anthropic, OpenAI
Composite Indices
Intelligence, Coding, Math
Standard Benchmarks
Academic and industry benchmarks
Benchmark Winners
Claude 4.1 Opus (Reasoning)
- MMLU Pro
GPT-5.2 (xhigh)
- GPQA
- HLE
- LiveCodeBench
- AIME 2025
| Metric | An Claude 4.1 Opus (Reasoning) | Op GPT-5.2 (xhigh) |
|---|---|---|
| Pricing Per 1M tokens | ||
| Input Cost | $15.00/1M | $1.75/1M |
| Output Cost | $75.00/1M | $14.00/1M |
| Blended Cost 3:1 input/output ratio | $30.00/1M | $4.81/1M |
| Specifications | ||
| Organization Model creator | Anthropic | OpenAI |
| Release Date Launch date | Aug 5, 2025 | Dec 11, 2025 |
| Performance & Speed | ||
| Throughput Output speed | 48.3 tok/s | 112.9 tok/s |
| Time to First Token (TTFT) Initial response delay | 1373ms | 42184ms |
| Latency Time to first answer token | 42778ms | 42184ms |
| Composite Indices | ||
| Intelligence Index Overall reasoning capability | 31.9 | 50.5 |
| Coding Index Programming ability | 35.1 | 46.7 |
| Math Index Mathematical reasoning | 80.3 | 99.0 |
| Standard Benchmarks | ||
| GPQA Graduate-level reasoning | 80.9% | 90.3% |
| MMLU Pro Advanced knowledge | 88.0% | 87.4% |
| HLE Hard language evaluation | 11.9% | 35.4% |
| LiveCodeBench Real-world coding tasks | 65.4% | 88.9% |
| MATH 500 Mathematical problems | — | — |
| AIME 2025 Advanced math competition | 80.3% | 99.0% |
| AIME (Original) Math olympiad problems | — | — |
| SciCode Scientific code generation | 40.9% | 52.1% |
| LCR Code review capability | 66.3% | 72.7% |
| IFBench Instruction-following | 55.4% | 75.4% |
| TAU-bench v2 Tool use & agentic tasks | 71.4% | 84.8% |
| TerminalBench Hard CLI command generation | 32.1% | 44.0% |
Key Takeaways
GPT-5.2 (xhigh) offers the best value at $1.75/1M, making it ideal for high-volume applications and cost-conscious projects.
GPT-5.2 (xhigh) leads in reasoning capabilities with a 90.3% GPQA score, excelling at complex analytical tasks and problem-solving.
GPT-5.2 (xhigh) achieves a 46.7 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Claude 4.1 Opus (Reasoning)
- General-purpose AI
- Versatile applications
GPT-5.2 (xhigh)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development