Meta
Llama 4 Scout 17B 16E
Frontier
425.5KDownloads1.3KLikesApr 2025Veröffentlicht10.5M TokenKontextLlama 4 CommunityLizenz66 GutQualität
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.
Loslegen
— kopieren & einfügen, um lokal auszuführenCopy-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
Verwandte Modelle
Schnellauswahl
Beste Hardware
Top-Empfehlungen für Llama 4 Scout 17B 16E
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
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
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights66.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — Llama 4 Scout 17B 16E
Siehe auch