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Gemma 3 12B Instruct

GoogleGemma开源权重Gemma · 商用许可

描述

Gemma 3 12B is a 12-billion-parameter vision-language model from Google, handling text and image input and generating text output. It features a 128K context window, multilingual support, and open weights. Suitable for question answering, summarization, reasoning, and image understanding tasks.

发布日期
2025-03-12
参数规模
12.0B
上下文长度
131K
支持模态
image, text

能力雷达图

22
general
10
coding
31
reasoning
23
science
25
agents
80
multimodal

排行榜排名

领域#排名分数来源
代码能力榜519
8.0
AA
通用能力榜474
25.0
AA
多模态榜57
43.0
LS
科学能力501
21.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)40.9%自报

Code

HumanEvalOpenAI (2021)85.4%自报
LiveCodeBench24.6%自报

Factuality

FACTS Grounding75.8%自报
SimpleQA6.3%自报

Finance

MMLU-Pro60.6%自报

General

IFEvalGoogle Research (2023)88.9%自报
Natural2Code80.7%自报
MBPP0.73 / 100自报
Global-MMLU-Lite69.5%自报
MMMU (val)59.6%自报
BIG-Bench Extra Hard16.3%自报

Image To Text

DocVQADocVQA (2020)87.1%自报
VQAv2 (val)71.6%自报
TextVQA67.7%自报

Language

BIG-Bench Hard85.7%自报
WMT24++51.6%自报
ECLeKTic10.3%自报

Math

GSM8k94.4%自报
MATH83.8%自报
MathVista-Mini62.9%自报
HiddenMath54.5%自报

Multimodal

AI2D84.2%自报
ChartQAMasry et al. (2022)75.7%自报
InfoVQA64.9%自报

Reasoning

Bird-SQL (dev)47.9%自报

AA 评测指数

(Artificial Analysis)
Math Index(Artificial Analysis)
18.3
Coding Index(Artificial Analysis)
5.8
Intelligence Index(Artificial Analysis)
5.5
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.6
Ifbench(Google Research (2023))
0.4
Gpqa(NYU + Cohere + Anthropic (2023))
0.3
Aime(MAA (Mathematical Association of America))
0.2
Aime 25(MAA (Mathematical Association of America))
0.2
Scicode(UIUC + Argonne National Lab (2024))
0.2
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.1
Lcr(Artificial Analysis)
0.1
Hle(Center for AI Safety + Scale AI (2025))
0.0
Tau Banking
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0
Terminalbench V2 1
0.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Structured Output
90
Instruction Following
90
Image To Text
80
Grounding
80
Math
70
Multimodal
70
Vision
70
Legal
60
Reasoning
60
Finance
60
General
60
Healthcare
60
Code
60
Language
50
Physics
40
Factuality
40
Biology
40
Chemistry
40

定价

输入价格免费
输出价格免费
混合价格(3:1)免费

速度

Tokens/秒0.0
首Token延迟0.00s
首回答延迟0.00s

供应商价格排行

供应商价格排行

1 个供应商

供应商输入输出
1Neon
$0.15
$0.5

比较该模型在不同 API 供应商之间的定价。

外部链接