Gemma 3 1B Instruct
GoogleGemmaOpen WeightGemma · Usage Commercial
Description
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.
Date de sortie
2025-03-13
Paramètres
1.0B
Longueur du contexte
—
Modalités
—
Radar de capacités
5
general
1
coding
11
reasoning
12
science
8
agents
0
multimodal
Classements
| Domaine | #Rang | Score | Source |
|---|---|---|---|
| Classement codage | 555 | 1.0 | AA |
| Classement général | 579 | 6.0 | AA |
| Science | 567 | 8.0 | AA |
Scores 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.
Indices d'évaluation 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
Scores par catégorie LLM Stats
(LLM Stats (zeroeval))Instruction Following80
Structured Output80
Math40
Grounding40
Reasoning30
General30
Language20
Physics20
Factuality20
Biology20
Chemistry20
Code20
Legal10
Finance10
Healthcare10
Tarification
Prix d'entréeGratuit
Prix de sortieGratuit
Prix mixte (3:1)Gratuit
Vitesse
Tokens/sec0.0
Délai du premier token0.00s
Temps de réponse0.00s
Classement des Prix par Fournisseur
Aucune donnée de fournisseur disponible