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Gemma 3n E4B Instruct

GoogleGemma開源權重Gemma · 商用許可

描述

Gemma 3n is a generative AI model optimized for use in everyday devices, such as phones, laptops, and tablets. It features innovations like Per-Layer Embedding (PLE) parameter caching and a MatFormer model architecture for reduced compute and memory. These models handle audio, text, and visual data, though this E4B preview currently supports text and vision input. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models, and is licensed for responsible commercial use.

發布日期
2025-06-26
參數規模
1.9B
上下文長度
33K
支援模態
image, text

能力雷達圖

16
general
13
coding
25
reasoning
17
science估算
21
agents
80
multimodal

Science 在缺少專門科學評測時使用推理能力代理估算。

排行榜排名

領域#排名分數來源
程式碼能力榜465
7.0
AA
通用能力榜476
16.0
AA
數學推理284
26.0
AA
推理能力35
79.0
LS
科學能力480
14.0
AA

基準測試分數 (LLM Stats)

Biology

GPQA23.7%自報

Code

HumanEval75.0%自報
Codegolf v2.216.8%自報
LiveCodeBench13.2%自報

Creativity

Social IQa50.0%自報

Finance

MMLU64.9%自報
MMLU-Pro50.6%自報
MMLU-ProX19.9%自報

General

ARC-E81.6%自報
PIQA81.0%自報
TriviaQA70.2%自報
Global-MMLU-Lite64.5%自報
MBPP0.64 / 100自報
ARC-C61.6%自報
Global-MMLU60.3%自報
Include57.2%自報
LiveCodeBench v525.7%自報
Natural Questions20.9%自報

Language

BoolQ81.6%自報
Winogrande71.7%自報
BIG-Bench Hard52.9%自報
WMT24++50.1%自報
ECLeKTic1.9%自報

Math

DROP60.8%自報
MGSM60.7%自報
HiddenMath37.7%自報
AIME 202511.6%自報

Reasoning

HellaSwag78.6%自報

AA 評測指數

Math Index
14.3
Intelligence Index
1.2
Math 500
0.8
Mmlu Pro
0.5
Gpqa
0.3
Ifbench
0.3
Livecodebench
0.1
Aime 25
0.1
Aime
0.1
Scicode
0.1
Tau2
0.0
Hle
0.0
Terminalbench Hard
0.0
Lcr
0.0

LLM Stats 分類評分

Language
50
Legal
50
Physics
50
Psychology
50
Reasoning
50
Finance
50
General
50
Healthcare
50
Creativity
50
Math
40
Code
40
Search
20
Biology
20
Chemistry
20

定價

輸入價格$0.02 / 1M tokens
輸出價格$0.04 / 1M tokens
混合價格(3:1)$0.025 / 1M tokens

速度

Tokens/秒53.6
首Token延遲0.52s
首回答延遲0.52s

供應商價格排行

供應商價格排行

2 個供應商

最便宜: Google最貴: Together AI
供應商輸入輸出
1Google主要
$0.02
$0.04
2Together AI
$0.06
$0.12

比較該模型在不同 API 供應商之間的定價。

外部連結