Gemma 3 12B Instruct
GoogleGemmaOpen WeightGemma · Uso Comercial
Descripción
Gemma 3 12B is a 12-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 question answering, summarization, reasoning, and image understanding tasks.
Fecha de lanzamiento
2025-03-12
Parámetros
12.0B
Longitud del contexto
131K
Modalidades
image, text
Radar de capacidades
21
general
10
coding
31
reasoning
22
science
25
agents
80
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 600 | 8.0 | AA |
| Ranking general | 565 | 22.0 | AA |
| Ranking multimodal | 119 | 38.0 | LS |
| Ciencia | 600 | 17.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Chat
IFEvalGoogle Research (2023)
88.9%Aut.
Factuality
SimpleQA
6.3%Aut.
General
Global-MMLU-Lite
69.5%Aut.
Language
MMLU-Pro
60.6%Aut.
WMT24++
51.6%Aut.
ECLeKTic
10.3%Aut.
Math
GSM8k
94.4%Aut.
MATH
83.8%Aut.
MathVista-Mini
62.9%Aut.
HiddenMath
54.5%Aut.
Reasoning
BIG-Bench Hard
85.7%Aut.
HumanEvalOpenAI (2021)
85.4%Aut.
Natural2Code
80.7%Aut.
FACTS Grounding
75.8%Aut.
ChartQAMasry et al. (2022)
75.7%Aut.
MBPP
0.73 / 100Aut.
Bird-SQL (dev)
47.9%Aut.
GPQANYU + Cohere + Anthropic (2023)
40.9%Aut.
LiveCodeBench
24.6%Aut.
BIG-Bench Extra Hard
16.3%Aut.
Vision
DocVQADocVQA (2020)
87.1%Aut.
AI2D
84.2%Aut.
VQAv2 (val)
71.6%Aut.
TextVQA
67.7%Aut.
InfoVQA
64.9%Aut.
MMMU (val)
59.6%Aut.
Índices de evaluación AA
(Artificial Analysis)Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))85.3
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))59.5
Ifbench(Google Research (2023))36.7
Gpqa(NYU + Cohere + Anthropic (2023))34.9
Aime(MAA (Mathematical Association of America))22.0
Aime 25(MAA (Mathematical Association of America))18.3
Math Index(Artificial Analysis)18.3
Scicode(UIUC + Argonne National Lab (2024))16.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))13.7
Tau2(Sierra + U Toronto + Vector Institute (2025))10.8
Lcr(Artificial Analysis)8.3
Coding Index(Artificial Analysis)5.8
Hle(Center for AI Safety + Scale AI (2025))4.2
Intelligence Index(Artificial Analysis)3.8
Tau Banking0.8
Terminalbench Hard(Stanford × Laude Institute (2026))0.8
Terminalbench V2 10.0
Terminalbench V4 00.0
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Chat90
Instruction Following90
Structured Output90
Image To Text80
Grounding80
Math70
Multimodal70
Vision70
Legal60
Reasoning60
Finance60
General60
Healthcare60
Code60
Language50
Physics40
Factuality40
Biology40
Chemistry40
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
Ranking de Precios por Proveedor
2 proveedores
Más barato: DeepInfraMás caro: Neon
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2Neon
$0.15
$0.5
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