LLMQwenMIT

Qwen3.5 122B-A10B

Qwen/Qwen3.5-122B-A10B

Parameters

122B

Context

256K

Downloads

2.1M

Likes

605

Architecture

moe_transformer

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
292.4 GB
RAM 438.6 · Disk 393.5
321.2 GB
RAM 481.8 · Disk 419.5
431.2 GB
RAM 646.8 · Disk 458.5
FP88bit
148.7 GB
RAM 223.0 · Disk 216.3
171.0 GB
RAM 256.5 · Disk 242.3
274.4 GB
RAM 411.6 · Disk 281.3
INT88bit
148.7 GB
RAM 223.0 · Disk 216.3
171.0 GB
RAM 256.5 · Disk 242.3
274.4 GB
RAM 411.6 · Disk 281.3
AWQ4bit
79.5 GB
RAM 119.3 · Disk 131.0
98.7 GB
RAM 148.0 · Disk 157.0
198.9 GB
RAM 298.4 · Disk 196.0
GPTQ4bit
80.4 GB
RAM 120.6 · Disk 132.1
99.6 GB
RAM 149.4 · Disk 158.1
199.9 GB
RAM 299.9 · Disk 197.1
GGUF4bit
82.2 GB
RAM 123.3 · Disk 134.3
101.5 GB
RAM 152.2 · Disk 160.3
201.9 GB
RAM 302.8 · Disk 199.3

GPU Recommendations

Best ValueBEST

4× H200 SXM

564 GB VRAM

$10,220/mo

≈ 195.5 tok/s

Effective production throughput ≈ 136.9 tok/s

score 0.316

Cheapest

8× Tesla V100

128 GB VRAM

$169/mo

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

Effective production throughput ≈ 0 tok/s

score 0.551

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 260.6 tok/s

Effective production throughput ≈ 182.4 tok/s

score 0.2197

Min Complexity

1× H200 SXM

141 GB VRAM

$2,555/mo

≈ 81.4 tok/s

Effective production throughput ≈ 57 tok/s

score 0.6576

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

View Community →

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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