GPT-5 (medium) vs Gemini 2.5 Pro
Comparing 2 AI models · 6 benchmarks · OpenAI, Google
Composite Indices
Intelligence, Coding, Math
Standard Benchmarks
Academic and industry benchmarks
Benchmark Winners
GPT-5 (medium)
- MMLU Pro
- HLE
- MATH 500
- AIME 2025
Gemini 2.5 Pro
- GPQA
- LiveCodeBench
| Metric | Op GPT-5 (medium) | Go Gemini 2.5 Pro |
|---|---|---|
| Pricing Per 1M tokens | ||
| Input Cost | $1.25/1M | $1.25/1M |
| Output Cost | $10.00/1M | $10.00/1M |
| Blended Cost 3:1 input/output ratio | $3.44/1M | $3.44/1M |
| Specifications | ||
| Organization Model creator | OpenAI | |
| Release Date Launch date | Aug 7, 2025 | Jun 5, 2025 |
| Performance & Speed | ||
| Throughput Output speed | — | 45.9 tok/s |
| Time to First Token (TTFT) Initial response delay | — | 15334ms |
| Latency Time to first answer token | — | 15334ms |
| Composite Indices | ||
| Intelligence Index Overall reasoning capability | 66.4 | 59.6 |
| Coding Index Programming ability | 49.2 | 49.3 |
| Math Index Mathematical reasoning | 91.7 | 87.7 |
| Standard Benchmarks | ||
| GPQA Graduate-level reasoning | 84.2% | 84.4% |
| MMLU Pro Advanced knowledge | 86.7% | 86.2% |
| HLE Hard language evaluation | 23.5% | 21.1% |
| LiveCodeBench Real-world coding tasks | 70.3% | 80.1% |
| MATH 500 Mathematical problems | 99.1% | 96.7% |
| AIME 2025 Advanced math competition | 91.7% | 87.7% |
| AIME (Original) Math olympiad problems | 91.7% | 88.7% |
| SciCode Scientific code generation | 41.1% | 42.8% |
| LCR Code review capability | 72.8% | 66.0% |
| IFBench Instruction-following | 70.6% | 48.7% |
| TAU-bench v2 Tool use & agentic tasks | 86.5% | 54.1% |
| TerminalBench Hard CLI command generation | 36.2% | 24.8% |
Key Takeaways
GPT-5 (medium) offers the best value at $1.25/1M, making it ideal for high-volume applications and cost-conscious projects.
Gemini 2.5 Pro leads in reasoning capabilities with a 84.4% GPQA score, excelling at complex analytical tasks and problem-solving.
Gemini 2.5 Pro achieves a 49.3 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
GPT-5 (medium)
- Cost-sensitive applications
- High-volume processing