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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
8
coding
25
reasoning
17
science
20
agents
80
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜522
5.0
AA
通用能力榜529
16.0
AA
科學能力532
14.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)23.7%自報

Chemistry

OpenAI MMLU35.6%自報

Code

HumanEvalOpenAI (2021)75.0%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

HellaSwagAI2 (2019)78.6%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
14.3
Coding Index(Artificial Analysis)
3.2
Intelligence Index(Artificial Analysis)
1.0
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.5
Gpqa(NYU + Cohere + Anthropic (2023))
0.3
Ifbench(Google Research (2023))
0.3
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.1
Aime 25(MAA (Mathematical Association of America))
0.1
Aime(MAA (Mathematical Association of America))
0.1
Scicode(UIUC + Argonne National Lab (2024))
0.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.0
Hle(Center for AI Safety + Scale AI (2025))
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0
Terminalbench V2 1
0.0
Tau Banking
0.0
Lcr(Artificial Analysis)
0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))
Legal
50
Physics
50
Psychology
50
Reasoning
50
Language
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$0.06 / 1M tokens
輸出價格$0.12 / 1M tokens
混合價格(3:1)$0.075 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

1 個供應商

供應商輸入輸出
1Google主要
$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