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
基準測試分數 (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
23.7%自報
Chemistry
OpenAI MMLU
35.6%自報
Code
HumanEvalOpenAI (2021)
75.0%自報
Codegolf v2.2
16.8%自報
LiveCodeBench
13.2%自報
Creativity
Social IQa
50.0%自報
Finance
MMLU
64.9%自報
MMLU-Pro
50.6%自報
MMLU-ProX
19.9%自報
General
ARC-E
81.6%自報
PIQA
81.0%自報
TriviaQA
70.2%自報
Global-MMLU-Lite
64.5%自報
MBPP
0.64 / 100自報
ARC-C
61.6%自報
Global-MMLU
60.3%自報
Include
57.2%自報
LiveCodeBench v5
25.7%自報
Natural Questions
20.9%自報
Language
BoolQ
81.6%自報
Winogrande
71.7%自報
BIG-Bench Hard
52.9%自報
WMT24++
50.1%自報
ECLeKTic
1.9%自報
Math
DROP
60.8%自報
MGSM
60.7%自報
HiddenMath
37.7%自報
AIME 2025
11.6%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 10.0
Tau Banking0.0
Lcr(Artificial Analysis)0.0
LLM Stats 分類評分
(LLM Stats (zeroeval))Legal50
Physics50
Psychology50
Reasoning50
Language50
Finance50
General50
Healthcare50
Creativity50
Math40
Code40
Search20
Biology20
Chemistry20
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。