Gemma 3 1B Instruct

GoogleGemma오픈 웨이트Gemma · 상업적 사용 가능

설명

The Gemma 3 1B model is a lightweight, 1-billion-parameter language model by Google, optimized for efficiency on resource-limited devices. At 529MB, it processes text at 2,585 tokens/second with a context window of 128,000 tokens. It supports 35+ languages but handles text-only input, unlike larger multimodal Gemma models. This balance of speed and efficiency makes it ideal for fast text processing on mobile and low-power devices.

출시일

2025-03-13

파라미터

1.0B

컨텍스트 길이

—

모달리티

—

능력 레이더

general

coding

reasoning

science

agents

multimodal

랭킹

도메인	#순위	점수	소스
코딩 랭킹	559	1.0	AA
종합 랭킹	583	6.0	AA
과학	571	8.0	AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)

19.2%자체 보고

Code

HumanEvalOpenAI (2021)

41.5%자체 보고

LiveCodeBench

1.9%자체 보고

Factuality

FACTS Grounding

36.4%자체 보고

SimpleQA

2.2%자체 보고

Finance

MMLU-Pro

14.7%자체 보고

General

IFEvalGoogle Research (2023)

80.2%자체 보고

Natural2Code

56.0%자체 보고

MBPP

0.35 / 100자체 보고

Global-MMLU-Lite

34.2%자체 보고

BIG-Bench Extra Hard

7.2%자체 보고

Language

BIG-Bench Hard

39.1%자체 보고

WMT24++

35.9%자체 보고

ECLeKTic

1.4%자체 보고

Math

GSM8k

62.8%자체 보고

MATH

48.0%자체 보고

HiddenMath

15.8%자체 보고

Reasoning

Bird-SQL (dev)

6.4%자체 보고

AA 평가 지수

(Artificial Analysis)

Math Index(Artificial Analysis)

3.3

Intelligence Index(Artificial Analysis)

1.0

Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))

0.5

Gpqa(NYU + Cohere + Anthropic (2023))

0.2

Ifbench(Google Research (2023))

0.2

Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))

0.1

Tau2(Sierra + U Toronto + Vector Institute (2025))

0.1

Hle(Center for AI Safety + Scale AI (2025))

0.1

Aime 25(MAA (Mathematical Association of America))

0.0

Livecodebench(UC Berkeley + MIT + Cornell (2024))

0.0

Scicode(UIUC + Argonne National Lab (2024))

0.0

Aime(MAA (Mathematical Association of America))

0.0

Lcr(Artificial Analysis)

0.0

Terminalbench Hard(Stanford × Laude Institute (2026))

0.0

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))

Structured Output

Instruction Following

Math

Grounding

Reasoning

General

Physics

Language

Factuality

Biology

Chemistry

Code

Legal

Finance

Healthcare

가격

입력 가격무료

출력 가격무료

혼합 가격 (3:1)무료

속도

토큰/초0.0

첫 토큰 지연0.00s

첫 응답 지연0.00s

공급자 가격 순위

프로바이더 데이터가 없습니다

외부 링크

LLM Stats Artificial Analysis