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Gemma 3 27B Instruct

GoogleGemma開源權重Gemma · 商用許可

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.

發布日期
2025-03-12
參數規模
27.0B
上下文長度
262K
支援模態
image, text

能力雷達圖

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

排行榜排名

領域#排名分數來源
程式碼能力榜495
11.0
AA
通用能力榜464
26.0
AA
多模態榜54
44.0
LS
科學能力461
27.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)42.4%自報

Code

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

Factuality

FACTS Grounding74.9%自報
SimpleQA10.0%自報

Finance

MMLU-Pro67.5%自報

General

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

Image To Text

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

Language

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

Math

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

Multimodal

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

Reasoning

Bird-SQL (dev)54.4%自報

AA 評測指數

(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 分類評分

(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

定價

輸入價格免費
輸出價格免費
混合價格(3:1)免費
快取讀取價格$0.04 / 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

6 個供應商

最便宜: OpenRouter最貴: STACKIT
供應商輸入輸出
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

比較該模型在不同 API 供應商之間的定價。

外部連結

LLM StatsArtificial Analysis