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Gemma 3 27B Instruct

GoogleGemma开源权重Gemma · 商用许可

描述

Gemma 3 27B is a 27-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 complex question answering, summarization, reasoning, and image understanding tasks.

发布日期
2025-03-12
参数规模
27.0B
上下文长度
131K
支持模态
image, text

能力雷达图

23
general
13
coding
34
reasoning
28
science
28
agents
70
multimodal

排行榜排名

领域#排名分数来源
代码能力榜568
11.0
AA
通用能力榜540
24.0
AA
多模态榜108
41.0
LS
科学能力540
23.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)90.4%自报

Factuality

SimpleQA10.0%自报

General

Global-MMLU-Lite75.1%自报

Language

MMLU-Pro67.5%自报
WMT24++53.4%自报
ECLeKTic16.7%自报

Long Context

MRCR v2 (8-needle)13.5%自报

Math

GSM8k95.9%自报
MATH89.0%自报
MathVista-Mini67.6%自报
HiddenMath60.3%自报

Reasoning

HumanEvalOpenAI (2021)87.8%自报
BIG-Bench Hard87.6%自报
Natural2Code84.5%自报
ChartQAMasry et al. (2022)78.0%自报
FACTS Grounding74.9%自报
MBPP0.74 / 100自报
Bird-SQL (dev)54.4%自报
GPQANYU + Cohere + Anthropic (2023)42.4%自报
LiveCodeBench29.7%自报
BIG-Bench Extra Hard19.3%自报

Vision

DocVQADocVQA (2020)86.6%自报
AI2D84.5%自报
VQAv2 (val)71.0%自报
InfoVQA70.6%自报
TextVQA65.1%自报
MMMU (val)64.9%自报

AA 评测指数

(Artificial Analysis)
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
88.3
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
66.9
Gpqa(NYU + Cohere + Anthropic (2023))
42.8
Ifbench(Google Research (2023))
31.8
Aime(MAA (Mathematical Association of America))
25.3
Scicode(UIUC + Argonne National Lab (2024))
23.3
Math Index(Artificial Analysis)
20.7
Aime 25(MAA (Mathematical Association of America))
20.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
13.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
10.5
Coding Index(Artificial Analysis)
10.1
Lcr(Artificial Analysis)
7.3
Intelligence Index(Artificial Analysis)
4.9
Terminalbench V2 1
4.5
Hle(Center for AI Safety + Scale AI (2025))
4.4
Terminalbench Hard(Stanford × Laude Institute (2026))
3.8
Tau Banking
0.8

LLM Stats 分类评分

(LLM Stats (zeroeval))
Chat
90
Instruction Following
90
Structured Output
90
Math
80
Image To Text
70
Legal
70
Multimodal
70
Finance
70
Grounding
70
Healthcare
70
Vision
70
Language
60
Reasoning
60
General
60
Code
60
Physics
40
Factuality
40
Biology
40
Chemistry
40
Long Context
10

定价

输入价格免费
输出价格免费
混合价格(3:1)免费
缓存读取价格$0.04 / 1M tokens

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

9 个供应商

最便宜: DeepInfra最贵: STACKIT
供应商输入输出
1DeepInfra最便宜
$0
$0
2OpenRouter
$0.08
$0.45
3Hugging Face
$0.08
$0.16
4Deep Infra
$0.08
$0.16
5Kilo Gateway
$0.08
$0.16
6Merge Gateway
$0.08
$0.45
7Nebius Token Factory
$0.1
$0.3
8NovitaAI
$0.119
$0.2
9STACKIT
$0.53
$0.76

比较该模型在不同 API 供应商之间的定价。

外部链接