gemma-3n-E4B-it-GGUF

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gemma-3n-E4B-it-GGUF

Mungert/gemma-3n-E4B-it-GGUF

kind: gguf
quant: gguf (16-bit)
family: gemma
modality: image-text-to-text
root model: google/gemma-3n-E4B
provider: Mungert
license: gemma
language: —
context: —
library: transformers
vRAM (GB): —
size on disk: —
downloads: 256
likes: 3
created: —
last modified: 2025-09-24T15:43:34+00:00 (2025)
huggingface: https://huggingface.co/Mungert/gemma-3n-E4B-it-GGUF
tags: transformersggufautomatic-speech-recognitionautomatic-speech-translationaudio-text-to-textvideo-text-to-textimage-text-to-textarxiv:1905.07830arxiv:1905.10044arxiv:1911.11641arxiv:1904.09728arxiv:1705.03551arxiv:1911.01547arxiv:1907.10641arxiv:1903.00161arxiv:2210.03057arxiv:2502.12404arxiv:2411.19799arxiv:2009.03300arxiv:2502.21228arxiv:2311.12022arxiv:2403.07974arxiv:2108.07732arxiv:2107.03374

Benchmark scores (20)

benchmark	category	score	context	conf	evidence
PIQA	knowledge	78.9	[PIQA][]	medium	`\| [PIQA][piqa] \| Accuracy \| 0-shot \| 78.9 \| 81.0 \|`
BoolQ	knowledge	76.4	[BoolQ][]	medium	`\| [BoolQ][boolq] \| Accuracy \| 0-shot \| 76.4 \| 81.6 \|`
HellaSwag	knowledge	72.2	[HellaSwag][]	medium	`\| [HellaSwag][hellaswag] \| Accuracy \| 10-shot \| 72.2 \| 78.6 \|`
WinoGrande	knowledge	66.8	[WinoGrande][]	medium	`\| [WinoGrande][winogrande] \| Accuracy \| 5-shot \| 66.8 \| 71.7 \|`
HumanEval	coding	66.5	[HumanEval][]	medium	`\| [HumanEval][humaneval] \| pass@1 \| 0-shot \| 66.5 \| 75.0 \|`
TriviaQA	knowledge	60.8	[TriviaQA][]	medium	`\| [TriviaQA][triviaqa] \| Accuracy \| 5-shot \| 60.8 \| 70.2 \|`
MMLU	knowledge	60.1	[MMLU][]	medium	`\| [MMLU][mmlu] \| Accuracy \| 0-shot \| 60.1 \| 64.9 \|`
MMLU	knowledge	59.0	[Global-MMLU-Lite][global--lite]	medium	`\| [Global-MMLU-Lite][global-mmlu-lite] \| Accuracy \| 0-shot \| 59.0 \| 64.5 \|`
MBPP	coding	56.6	[MBPP][]	medium	`\| [MBPP][mbpp] \| pass@1 \| 3-shot \| 56.6 \| 63.6 \|`
MMLU	knowledge	55.1	[Global-MMLU][global-]	medium	`\| [Global-MMLU][global-mmlu] \| Accuracy \| 0-shot \| 55.1 \| 60.3 \|`
DROP	reasoning	53.9	[DROP][]	medium	`\| [DROP][drop] \| Token F1 score \| 1-shot \| 53.9 \| 60.8 \|`
MGSM	math	53.1	[MGSM][]	medium	`\| [MGSM][mgsm] \| Accuracy \| 0-shot \| 53.1 \| 60.7 \|`
BBH	reasoning	44.3	[BIG-Bench Hard][]	medium	`\| [BIG-Bench Hard][bbh] \| Accuracy \| few-shot \| 44.3 \| 52.9 \|`
MMLU	knowledge	40.5	[MMLU][] (Pro)	medium	`\| [MMLU][mmlu] (Pro) \| Accuracy \| 0-shot \| 40.5 \| 50.6 \|`
GPQA	reasoning	24.8	[GPQA][] Diamond	medium	`\| [GPQA][gpqa] Diamond \| RelaxedAccuracy/accuracy \| 0-shot \| 24.8 \| 23.7 \|`
MMLU	knowledge	22.3	[OpenAI MMLU][openai-]	medium	`\| [OpenAI MMLU][openai-mmlu] \| Accuracy \| 0-shot \| 22.3 \| 35.6 \|`
LiveCodeBench	coding	18.6	[LiveCodeBench][lcb] v5	medium	`\| [LiveCodeBench][lcb] v5 \| pass@1 \| 0-shot \| 18.6 \| 25.7 \|`
LiveCodeBench	coding	13.2	[LiveCodeBench][lcb]	medium	`\| [LiveCodeBench][lcb] \| pass@1 \| 0-shot \| 13.2 \| 13.2 \|`
MMLU	knowledge	8.1	[MMLU][] (ProX)	medium	`\| [MMLU][mmlu] (ProX) \| Accuracy \| 0-shot \| 8.1 \| 19.9 \|`
AIME 2025	math	6.7	[AIME 2025][]	medium	`\| [AIME 2025][aime-2025] \| Accuracy \| 0-shot \| 6.7 \| 11.6 \|`

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