Gemma 3 12B

Gemma 3 12B is a 12-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 question answering, summarization, reasoning, and image understanding tasks.

Benchmark results

Benchmark Score Tags Source
AI2D 84.2% self-reported llm-stats link →
BIG-Bench Extra Hard 16.3% self-reported llm-stats link →
BIG-Bench Hard 85.7% self-reported llm-stats link →
Bird-SQL (dev) 47.9% self-reported llm-stats link →
ChartQA 75.7% self-reported llm-stats link →
DocVQA 87.1% self-reported llm-stats link →
ECLeKTic 10.3% self-reported llm-stats link →
FACTS Grounding 75.8% self-reported llm-stats link →
Global-MMLU-Lite 69.5% self-reported llm-stats link →
GPQA 40.9% self-reported llm-stats link →
GSM8k 94.4% self-reported llm-stats link →
HiddenMath 54.5% self-reported llm-stats link →
HumanEval 85.4% self-reported llm-stats link →
IFEval 88.9% self-reported llm-stats link →
InfoVQA 64.9% self-reported llm-stats link →
LiveCodeBench 24.6% self-reported llm-stats link →
MATH 83.8% self-reported llm-stats link →
MathVista-Mini 62.9% self-reported llm-stats link →
MBPP 73.0% self-reported llm-stats link →
MMLU-Pro 60.6% self-reported llm-stats link →
MMMU (val) 59.6% self-reported llm-stats link →
Natural2Code 80.7% self-reported llm-stats link →
SimpleQA 6.3% self-reported llm-stats link →
TextVQA 67.7% self-reported llm-stats link →
VQAv2 (val) 71.6% self-reported llm-stats link →
WMT24++ 51.6% self-reported llm-stats link →