Gemma 3 1B Instruct
GoogleGemmaOpen WeightGemma · Uso Comercial
Descripción
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.
Fecha de lanzamiento
2025-03-13
Parámetros
1.0B
Longitud del contexto
—
Modalidades
—
Radar de capacidades
5
general
1
coding
11
reasoning
12
science
8
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 559 | 1.0 | AA |
| Ranking general | 583 | 6.0 | AA |
| Ciencia | 571 | 8.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
19.2%Aut.
Code
HumanEvalOpenAI (2021)
41.5%Aut.
LiveCodeBench
1.9%Aut.
Factuality
FACTS Grounding
36.4%Aut.
SimpleQA
2.2%Aut.
Finance
MMLU-Pro
14.7%Aut.
General
IFEvalGoogle Research (2023)
80.2%Aut.
Natural2Code
56.0%Aut.
MBPP
0.35 / 100Aut.
Global-MMLU-Lite
34.2%Aut.
BIG-Bench Extra Hard
7.2%Aut.
Language
BIG-Bench Hard
39.1%Aut.
WMT24++
35.9%Aut.
ECLeKTic
1.4%Aut.
Math
GSM8k
62.8%Aut.
MATH
48.0%Aut.
HiddenMath
15.8%Aut.
Reasoning
Bird-SQL (dev)
6.4%Aut.
Índices de evaluación AA
(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
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Structured Output80
Instruction Following80
Math40
Grounding40
Reasoning30
General30
Physics20
Language20
Factuality20
Biology20
Chemistry20
Code20
Legal10
Finance10
Healthcare10
Precios
Precio de entradaGratis
Precio de salidaGratis
Precio mixto (3:1)Gratis
Velocidad
Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s
Ranking de Precios por Proveedor
No hay datos de proveedores disponibles