Gemma 是 Google 基于 Gemini 技术构建的轻量级模型系列。Gemma 3 模型是多模态的(可处理文本和图片),具有 128K
上下文窗口,支持 140 多种语言。Gemma 3 提供 1b 4b 12b 和 27b 的参数大小,在问答、总结和推理等任务中表现出色,其紧凑的设计使其可以在资源有限的设备上部署。
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Gemma 3
这些模型根据大量不同的数据集和指标进行评估,以涵盖文本生成的不同方面,包括:推理、逻辑和代码能力
Benchmark | Metric | Gemma 3 PT 1B | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
---|---|---|---|---|---|
HellaSwag | 10-shot | 62.3 | 77.2 | 84.2 | 85.6 |
BoolQ | 0-shot | 63.2 | 72.3 | 78.8 | 82.4 |
PIQA | 0-shot | 73.8 | 79.6 | 81.8 | 83.3 |
SocialIQA | 0-shot | 48.9 | 51.9 | 53.4 | 54.9 |
TriviaQA | 5-shot | 39.8 | 65.8 | 78.2 | 85.5 |
Natural Questions | 5-shot | 9.48 | 20.0 | 31.4 | 36.1 |
ARC-c | 25-shot | 38.4 | 56.2 | 68.9 | 70.6 |
ARC-e | 0-shot | 73.0 | 82.4 | 88.3 | 89.0 |
WinoGrande | 5-shot | 58.2 | 64.7 | 74.3 | 78.8 |
BIG-Bench Hard | 28.4 | 50.9 | 72.6 | 77.7 | |
DROP | 3-shot, F1 | 42.4 | 60.1 | 72.2 | 77.2 |
AGIEval | 3-5-shot | 22.2 | 42.1 | 57.4 | 66.2 |
MMLU | 5-shot, top-1 | 26.5 | 59.6 | 74.5 | 78.6 |
MATH | 4-shot | – | 24.2 | 43.3 | 50.0 |
GSM8K | 5-shot, maj@1 | 1.36 | 38.4 | 71.0 | 82.6 |
GPQA | 9.38 | 15.0 | 25.4 | 24.3 | |
MMLU (Pro) | 5-shot | 11.2 | 23.7 | 40.8 | 43.9 |
MBPP | 3-shot | 9.80 | 46.0 | 60.4 | 65.6 |
HumanEval | pass@1 | 6.10 | 36.0 | 45.7 | 48.8 |
MMLU (Pro COT) | 5-shot | 9.7 | NaN | NaN | NaN |
Benchmark | Gemma 3 PT 1B | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
---|---|---|---|---|
MGSM | 2.04 | 34.7 | 64.3 | 74.3 |
Global-MMLU-Lite | 24.9 | 57.0 | 69.4 | 75.7 |
Belebele | 26.6 | 59.4 | 78.0 | – |
WMT24++ (ChrF) | 36.7 | 48.4 | 53.9 | 55.7 |
FloRes | 29.5 | 39.2 | 46.0 | 48.8 |
XL-Sum | 4.82 | 8.55 | 12.2 | 14.9 |
XQuAD (all) | 43.9 | 68.0 | 74.5 | 76.8 |
Benchmark | Gemma 3 PT 4B | Gemma 3 PT 12B | Gemma 3 PT 27B |
---|---|---|---|
COCOcap | 102 | 111 | 116 |
DocVQA (val) | 72.8 | 82.3 | 85.6 |
InfoVQA (val) | 44.1 | 54.8 | 59.4 |
MMMU (pt) | 39.2 | 50.3 | 56.1 |
TextVQA (val) | 58.9 | 66.5 | 68.6 |
RealWorldQA | 45.5 | 52.2 | 53.9 |
ReMI | 27.3 | 38.5 | 44.8 |
AI2D | 63.2 | 75.2 | 79.0 |
ChartQA | 45.4 | 60.9 | 63.8 |
ChartQA (augmented) | 81.8 | 88.5 | 88.7 |
VQAv2 | – | – | – |
BLINK | 38.0 | 35.9 | 39.6 |
OKVQA | 51.0 | 58.7 | 60.2 |
TallyQA | 42.5 | 51.8 | 54.3 |
SpatialSense VQA | 50.9 | 60.0 | 59.4 |
CountBenchQA | 26.1 | 17.8 | 68.0 |