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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

21
general
10
coding
31
reasoning
22
science
25
agents
80
multimodal

排行榜排名

领域#排名分数来源
代码能力榜600
8.0
AA
通用能力榜565
22.0
AA
多模态榜119
38.0
LS
科学能力600
17.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)88.9%自报

Factuality

SimpleQA6.3%自报

General

Global-MMLU-Lite69.5%自报

Language

MMLU-Pro60.6%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

Reasoning

BIG-Bench Hard85.7%自报
HumanEvalOpenAI (2021)85.4%自报
Natural2Code80.7%自报
FACTS Grounding75.8%自报
ChartQAMasry et al. (2022)75.7%自报
MBPP0.73 / 100自报
Bird-SQL (dev)47.9%自报
GPQANYU + Cohere + Anthropic (2023)40.9%自报
LiveCodeBench24.6%自报
BIG-Bench Extra Hard16.3%自报

Vision

DocVQADocVQA (2020)87.1%自报
AI2D84.2%自报
VQAv2 (val)71.6%自报
TextVQA67.7%自报
InfoVQA64.9%自报
MMMU (val)59.6%自报

AA 评测指数

(Artificial Analysis)
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
85.3
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
59.5
Ifbench(Google Research (2023))
36.7
Gpqa(NYU + Cohere + Anthropic (2023))
34.9
Aime(MAA (Mathematical Association of America))
22.0
Aime 25(MAA (Mathematical Association of America))
18.3
Math Index(Artificial Analysis)
18.3
Scicode(UIUC + Argonne National Lab (2024))
16.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))
13.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
10.8
Lcr(Artificial Analysis)
8.3
Coding Index(Artificial Analysis)
5.8
Hle(Center for AI Safety + Scale AI (2025))
4.2
Intelligence Index(Artificial Analysis)
3.8
Tau Banking
0.8
Terminalbench Hard(Stanford × Laude Institute (2026))
0.8
Terminalbench V2 1
0.0
Terminalbench V4 0
0.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Chat
90
Instruction Following
90
Structured Output
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

2 个供应商

最便宜: DeepInfra最贵: Neon
供应商输入输出
1DeepInfra最便宜
$0
$0
2Neon
$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