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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
262K
支持模态
image, text

能力雷达图

25
general
12
coding
34
reasoning
28
science
27
agents
70
multimodal

排行榜排名

领域#排名分数来源
代码能力榜495
11.0
AA
通用能力榜464
26.0
AA
多模态榜54
44.0
LS
科学能力461
27.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)42.4%自报

Code

HumanEvalOpenAI (2021)87.8%自报
LiveCodeBench29.7%自报

Factuality

FACTS Grounding74.9%自报
SimpleQA10.0%自报

Finance

MMLU-Pro67.5%自报

General

IFEvalGoogle Research (2023)90.4%自报
Natural2Code84.5%自报
Global-MMLU-Lite75.1%自报
MBPP0.74 / 100自报
MMMU (val)64.9%自报
BIG-Bench Extra Hard19.3%自报
MRCR v2 (8-needle)13.5%自报

Image To Text

DocVQADocVQA (2020)86.6%自报
VQAv2 (val)71.0%自报
TextVQA65.1%自报

Language

BIG-Bench Hard87.6%自报
WMT24++53.4%自报
ECLeKTic16.7%自报

Math

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

Multimodal

AI2D84.5%自报
ChartQAMasry et al. (2022)78.0%自报
InfoVQA70.6%自报

Reasoning

Bird-SQL (dev)54.4%自报

AA 评测指数

(Artificial Analysis)
Math Index(Artificial Analysis)
20.7
Coding Index(Artificial Analysis)
10.1
Intelligence Index(Artificial Analysis)
7.4
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.4
Ifbench(Google Research (2023))
0.3
Aime(MAA (Mathematical Association of America))
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.2
Aime 25(MAA (Mathematical Association of America))
0.2
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.1
Lcr(Artificial Analysis)
0.1
Terminalbench V2 1
0.0
Hle(Center for AI Safety + Scale AI (2025))
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0
Tau Banking
0.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Structured Output
90
Instruction Following
90
Math
80
Legal
70
Multimodal
70
Image To Text
70
Finance
70
Grounding
70
Healthcare
70
Vision
70
Reasoning
60
Language
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

6 个供应商

最便宜: OpenRouter最贵: STACKIT
供应商输入输出
1OpenRouter最便宜
$0.08
$0.45
2Kilo Gateway
$0.08
$0.16
3Nebius Token Factory
$0.1
$0.3
4LLM Gateway
$0.1
$0.3
5NovitaAI
$0.119
$0.2
6STACKIT
$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

LLM StatsArtificial Analysis