Google has officially announced Gemini 3.0, the newest flagship model in its generative AI lineup, focusing heavily on scientific reasoning, mathematics, multimodal understanding and long-horizon agentic tasks. Early benchmark data shows that Gemini 3.0 improves significantly over Gemini 2.5 Pro and posts competitive, often superior, performance against GPT-5.1 across several categories.
Gemini 3.0’s strongest gains are visible in tasks involving scientific knowledge (GPQA Diamond), math competitions, agentic tool use, coding benchmarks, and long-horizon decision-making. The model also delivers major improvements in multimodal reasoning benchmarks such as MMMU-Pro and ScreenSpot-Pro, marking a step-change for interactive and real-time use cases.
Benchmark comparison table: Gemini 3.0 vs Gemini 2.5 Pro vs GPT-5.1| Benchmark | Description | Gemini 3.0 | Gemini 2.5 Pro | GPT-5.1 |
|---|---|---|---|---|
| Humanity’s Last Exam | Academic reasoning | 37.5% (no tools) / 45.8% (search + execution) | 21.6% | 26.5% |
| ARC-AGI-2 | Visual reasoning puzzles | 31.1% | 4.9% | 17.6% |
| GPQA Diamond | Scientific knowledge | 91.9% | 86.4% | 88.1% |
| AIME 2025 | Mathematics | 95.0% | 88.0% | 94.0% |
| MathArena Apex | Math contest problems | 23.4% | 0.5% | 1.0% |
| MMMU-Pro | Multimodal reasoning | 81.0% | 68.0% | 76.0% |
| ScreenSpot-Pro | Screen understanding | 72.7% | 11.4% | 3.5% |
| CharXiv Reasoning | Chart/complex info synthesis | 81.4% | 69.6% | 69.5% |
| OmniDocBench 1.5 | OCR (lower is better) | 0.115 | 0.145 | 0.147 |
| Video-MMMU | Video knowledge | 87.6% | 83.6% | 80.4% |
| LiveCodeBench Pro | Competitive coding | 2,439 | 1,775 | 2,243 |
| Terminal-Bench 2.0 | Agentic terminal coding | 54.2% | 32.6% | 47.6% |
| SWE-Bench Verified | Agentic coding | 76.2% | 59.6% | 76.3% |
| t2-bench | Agentic tool use | 85.4% | 54.9% | 80.2% |
| Vending-Bench 2 | Long-horizon decision tasks | $5,478.16 | $573.64 | $1,473.43 |
| FACTS Benchmark Suite | Grounding + parametric reasoning | 70.5% | 63.4% | 50.8% |
| SimpleQA Verified | Parametric knowledge | 72.1% | 54.5% | 34.9% |
| MMLU | Multilingual Q&A | 91.8% | 89.5% | 91.0% |
| Global PIQA | Commonsense reasoning | 93.4% | 91.5% | 90.9% |
| MRCR V2 (8-needle) | Long-context performance | 77.0% | 58.0% | 61.6% |
| MRCR V2 (1M pointwise) | Long-context | 26.3% | 16.4% | not supported |
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