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Llama 4 Scout 17B 16E
最先端
425.5Kダウンロード1.3KいいねApr 2025公開日10.5M トークンコンテキストLlama 4 Communityライセンス66 良好品質
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.
はじめに
— コピー&ペーストでローカル実行Copy-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
関連モデル
おすすめ
最適なハードウェア
Llama 4 Scout 17B 16Eのおすすめ
このモデルを実行
量子化オプション
量子化レベル別VRAM推定値
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
ハードウェア互換性
全ハードウェアの適合度推定
Computing compatibility...
メモリ内訳
Reference: RTX 2060 6GB
Weights66.5 GB
KV Cache2.9 GB
Runtime1.2 GB
Headroom0.6 GB
よくある質問
FAQ — Llama 4 Scout 17B 16E
関連項目