LLMLlamaMIT

Llama 4 Scout

meta-llama/Llama-4-Scout-17B-16E-Instruct

Parameters

109B

Context

10240K

Downloads

460.4K

Likes

1.3K

Architecture

moe_transformer

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
261.8 GB
RAM 392.7 · Disk 355.7
289.2 GB
RAM 433.8 · Disk 381.7
397.8 GB
RAM 596.7 · Disk 420.7
FP88bit
133.4 GB
RAM 200.1 · Disk 197.4
155.0 GB
RAM 232.4 · Disk 223.4
257.7 GB
RAM 386.5 · Disk 262.4
INT88bit
133.4 GB
RAM 200.1 · Disk 197.4
155.0 GB
RAM 232.4 · Disk 223.4
257.7 GB
RAM 386.5 · Disk 262.4
AWQ4bit
71.6 GB
RAM 107.4 · Disk 121.2
90.3 GB
RAM 135.5 · Disk 147.2
190.3 GB
RAM 285.4 · Disk 186.2
GPTQ4bit
72.4 GB
RAM 108.6 · Disk 122.1
91.2 GB
RAM 136.8 · Disk 148.1
191.2 GB
RAM 286.7 · Disk 187.1
GGUF4bit
74.0 GB
RAM 111.0 · Disk 124.1
92.9 GB
RAM 139.3 · Disk 150.1
192.9 GB
RAM 289.4 · Disk 189.1

GPU Recommendations

Best ValueBEST

4× H200 SXM

564 GB VRAM

$10,220/mo

≈ 218.8 tok/s

Effective production throughput ≈ 153.2 tok/s

score 0.3121

Cheapest

8× Tesla V100

128 GB VRAM

$169/mo

≈ 0 tok/s (N/A — benchmark unavailable)

Effective production throughput ≈ 0 tok/s

score 0.5447

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 291.7 tok/s

Effective production throughput ≈ 204.2 tok/s

score 0.2197

Min Complexity

1× H200 SXM

141 GB VRAM

$2,555/mo

≈ 91.2 tok/s

Effective production throughput ≈ 63.8 tok/s

score 0.6419

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

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GPUs that fit (single card)

H200 SXM

141 GB VRAM

$2,555

/mo · lambda

B200

180 GB VRAM

$3,013

/mo · vast

B200 SXM

180 GB VRAM

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