Gemma 3 27B
Gemma 3 27B is a 27-billion-parameter vision-language model from Google, handling text and image input and generating text output. It features a 128K context window, multilingual support, and open weights. Suitable for complex question answering, summarization, reasoning, and image understanding tasks.
Benchmark results
| Benchmark | Score | Tags | Source |
|---|---|---|---|
| AI2D | 84.5% | self-reported llm-stats | link → |
| BIG-Bench Extra Hard | 19.3% | self-reported llm-stats | link → |
| BIG-Bench Hard | 87.6% | self-reported llm-stats | link → |
| Bird-SQL (dev) | 54.4% | self-reported llm-stats | link → |
| ChartQA | 78.0% | self-reported llm-stats | link → |
| DocVQA | 86.6% | self-reported llm-stats | link → |
| ECLeKTic | 16.7% | self-reported llm-stats | link → |
| FACTS Grounding | 74.9% | self-reported llm-stats | link → |
| Global-MMLU-Lite | 75.1% | self-reported llm-stats | link → |
| GPQA | 42.4% | self-reported llm-stats | link → |
| GSM8k | 95.9% | self-reported llm-stats | link → |
| HiddenMath | 60.3% | self-reported llm-stats | link → |
| HumanEval | 87.8% | self-reported llm-stats | link → |
| IFEval | 90.4% | self-reported llm-stats | link → |
| InfoVQA | 70.6% | self-reported llm-stats | link → |
| LiveCodeBench | 29.7% | self-reported llm-stats | link → |
| MATH | 89.0% | self-reported llm-stats | link → |
| MathVista-Mini | 67.6% | self-reported llm-stats | link → |
| MBPP | 74.4% | self-reported llm-stats | link → |
| MMLU-Pro | 67.5% | self-reported llm-stats | link → |
| MMMU (val) | 64.9% | self-reported llm-stats | link → |
| Natural2Code | 84.5% | self-reported llm-stats | link → |
| SimpleQA | 10.0% | self-reported llm-stats | link → |
| TextVQA | 65.1% | self-reported llm-stats | link → |
| VQAv2 (val) | 71.0% | self-reported llm-stats | link → |
| WMT24++ | 53.4% | self-reported llm-stats | link → |