gemma3

The current strongest model that fits on a single GPU.

1b 4b 12b 27b

223.6K 5 hours ago

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This model requires Ollama 0.6 or later. Download Ollama

Gemma is a lightweight, family of models from Google built on Gemini technology. The Gemma 3 models are multimodal—processing text and images—and feature a 128K context window with support for over 140 languages. Available in 1B, 4B, 12B, and 27B parameter sizes, they excel in tasks like question answering, summarization, and reasoning, while their compact design allows deployment on resource-limited devices.

Models

Text

1B parameter model (32k context window)

ollama run gemma3:1b

Multimodal (Vision)

4B parameter model (128k context window)

ollama run gemma3:4b

12B parameter model (128k context window)

ollama run gemma3:12b

27B parameter model (128k context window)

ollama run gemma3:27b

Evaluation

Chatbot Arena ELO Score

Benchmark Results

These models were evaluated against a large collection of different datasets and metrics to cover different aspects of text generation:

Reasoning, logic and code capabilities

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

Multilingual capabilities

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

Multimodal capabilities

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