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Llama 4 Scout 17B 16E
Frontera
425.5KDescargas1.3KMe gustaApr 2025Publicado10.5M tokensContextoLlama 4 CommunityLicencia66 BuenoCalidad
Llama 4 Scout 17B 16E (109B parameters) requires approximately 71.2 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 17B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 82 GB of VRAM.
Comenzar
— copia y pega para ejecutar en localCopy-paste commands to run Llama 4 Scout 17B 16E on your machine.
Run
lms load Llama-4-Scout-17B-16E-Instruct && lms server startQuick specs
Parameters109B (17B active)
Architecturemoe (MoE)
Context10.5M tokens
Modalitytext+vision
Min RAM42.5 GB
Rec. RAM66.5 GB (Q4_K_M)
LicenseLlama 4 Community
FamilyLlama
✓ Vision✓ Chat✓ Reasoning
About this model
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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 | 42.5 GB | Low | — |
Q3_K_S | 3 | 53.4 GB | Low | — |
NVFP4 | 4 | 61.0 GB | Medium | — |
Q4_K_M | 4 | 66.5 GB | Medium | — |
Q5_K_M | 5 | 78.5 GB | High | — |
Q6_K | 6 | 89.4 GB | High | — |
Q8_0 | 8 | 116.6 GB | Very High | — |
F16 | 16 | 223.5 GB | Maximum | — |
Quality benchmarks
Llama 4 Scout 17B 16E benchmark scores
Coding
SWE-bench Verified—
HumanEval+—
Aider Polyglot—
LiveCodeBench32.8%
Reasoning
MMLU-Pro74.3%
GPQA Diamond57.2%
MATH-50050.3%
ARC Challenge—
Source: official · 2025-04-05
Compatibilidad de hardware
Estimaciones de encaje en todo el hardware
Computing compatibility...
Desglose de memoria
Reference: RTX 2060 6GB
Weights66.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB
Preguntas frecuentes
FAQ — Llama 4 Scout 17B 16E
Ver también