Ubergarm Q5_K 122B Parameters

VRAM Requirements for
Qwen3.5-122B-A10B-GGUF Q5_K

To run Qwen3.5-122B-A10B-GGUF locally at Q5_K quantization, you need at minimum 87.88 GB of GPU VRAM.

87.88 GB
Required VRAM
83.88 GB
File Size
8K tokens
Context Window
122B
Parameters
Estimated VRAM Required
87.88
GB
Cluster Required
0 16GB
RTX 3080 48GB
A6000 80GB+

Recommended GPU Configurations

Budget $40,000+

4× A100 40GB Cluster

160 GB

Distributed inference across 4 A100s. Minimum viable cluster.

Balanced $60,000+

2× H100 80GB NVLink

160 GB HBM3

NVLink bridge enables unified 160GB VRAM pool.

Ultimate $3,000,000+

NVIDIA GB200 NVL72

1.4 TB HBM3e

Next-gen Grace Blackwell Superchip. Built for frontier models.

📊 VRAM Calculation Breakdown

Model File Size (Q5_K) 83.88 GB
Context Overhead (8,192 tokens × 122B × 2 ÷ 1M) 1.999 GB
System Buffer (OS + CUDA runtime) 2.00 GB
Total Required VRAM 87.88 GB

Try a Different Quantization

Use the interactive calculator to compare Qwen3.5-122B-A10B-GGUF across all available formats.

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Qwen3.5-122B-A10B-GGUF — Other Quantizations

Q2_K 38.13 GB file
42.13 GB
Q4_K 68.63 GB file
72.63 GB
Q5_K Current
87.88 GB
Q1_K 122 GB file
126 GB
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Frequently Asked Questions

Can I run Qwen3.5-122B-A10B-GGUF Q5_K on a consumer GPU?
Running Qwen3.5-122B-A10B-GGUF Q5_K locally requires 87.88 GB VRAM, which exceeds consumer GPUs. You'll need prosumer cards like the NVIDIA A6000 (48GB) or an A100 (80GB).
What happens if I don't have enough VRAM?
If your GPU VRAM is insufficient, llama.cpp and similar tools will offload model layers to system RAM (CPU inference). This is much slower — expect 10-50× the generation latency compared to full GPU inference.
Can I use multiple GPUs to run Qwen3.5-122B-A10B-GGUF?
Yes! Tools like llama.cpp, vLLM, and Ollama support tensor parallelism across multiple GPUs. For example, 2× RTX 3090 (24GB each) gives you 48GB total VRAM, which can run many large models.
Is Q5_K quality good enough for production?
Q5_K is suitable for specialized use cases. Check community benchmarks for specific quality metrics.