HuggingFace
SmolLM3 3B
423.9KDescargas961Me gustaJul 2025Publicado128K tokensContextoApache 2.0Licencia21 EntradaCalidad
SmolLM3 3B (3B parameters) requires approximately 5.6 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 7 GB of VRAM.
Comenzar
— copia y pega para ejecutar en localCopy-paste commands to run SmolLM3 3B on your machine.
Run
lms load SmolLM3-3B && lms server startQuick specs
Parameters3B
Architecturedense
Context128K tokens
Modalitytext
Min RAM1.2 GB
Rec. RAM1.8 GB (Q4_K_M)
LicenseApache 2.0
FamilySmolLM
✓ Chat✓ Reasoning
About this model
- •Dual-mode reasoning: extended thinking can be toggled on/off
- •128K context via YARN extrapolation from 64K training
- •6 natively supported languages: English, French, Spanish, German, Italian, Portuguese
- •Fully open: weights, training details, and public data mixture
Selecciones rápidas
Mejor hardware
Mejores opciones para SmolLM3 3B
Ejecutar este modelo
Opciones de cuantización
Estimaciones de VRAM por nivel de cuantización
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | — |
Q3_K_S | 3 | 1.5 GB | Low | — |
NVFP4 | 4 | 1.7 GB | Medium | — |
Q4_K_M | 4 | 1.8 GB | Medium | — |
Q5_K_M | 5 | 2.2 GB | High | — |
Q6_K | 6 | 2.5 GB | High | — |
Q8_0 | 8 | 3.2 GB | Very High | — |
F16 | 16 | 6.1 GB | Maximum | — |
Quality benchmarks
SmolLM3 3B benchmark scores
Coding
SWE-bench Verified—
HumanEval+30.5%
Aider Polyglot—
LiveCodeBench—
Reasoning
MMLU-Pro32.7%
GPQA Diamond35.7%
MATH-500—
ARC Challenge—
General
Chatbot Arena—
IFEval76.7%
Source: official · 2025-07-02
Compatibilidad de hardware
Estimaciones de encaje en todo el hardware
Computing compatibility...
Desglose de memoria
Reference: RTX 2060 6GB
Weights1.8 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom0.6 GB
Preguntas frecuentes
FAQ — SmolLM3 3B
Ver también