How much VRAM does Qwen3.5 27B need?

Qwen3.5 27B (27B parameters) requires approximately 22.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3.5 27B?

The recommended quantization for Qwen3.5 27B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

No, Qwen3.5 27B requires more memory than RTX 2060 Super 8GB provides.

FWon't run

Too heavy

Using Q4_K_M in Ollama

Capabilities:

Fit status

Too heavy

Decode

19.6 tok/s

TTFT

9885 ms

Safe context

Memory

22.7 GB / 8.0 GB

Weights16.5 GB

KV Cache4.2 GB

Runtime1.2 GB

Headroom0.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	F	Too heavy	15.8 tok/s	17849 ms	10K
Chat	F	Too heavy	15.8 tok/s	6693 ms	4K
Coding	F	Too heavy	19.6 tok/s	9885 ms	6K
RAG	F	Too heavy	15.8 tok/s	22312 ms	10K
Reasoning	F	Too heavy	15.8 tok/s	14503 ms	6K

How Qwen3.5 27B (27B params) fits at each quantization level on RTX 2060 Super 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	10.5 GB	Low	F0
Q3_K_S	3	13.2 GB	Low	F0
NVFP4	4

Upgrade options

RX 7900 XTX 24GBBest value

C41.5 tok/s decode

~$999 MSRP

Mac mini M4 64GBBudget pick

C5.2 tok/s decode

~$1,099 MSRP

RTX 5090 32GBBiggest leap