How much VRAM does Qwen3.5 9B need?

Qwen3.5 9B (9B parameters) requires approximately 14.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3.5 9B?

The recommended quantization for Qwen3.5 9B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, NVIDIA A16 64GB can run Qwen3.5 9B with a C grade (Runs well). Expected decode speed: 85.2 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

85.2 tok/s

TTFT

2271 ms

Safe context

71K

Memory

14.5 GB / 64.0 GB

Weights5.5 GB

KV Cache1.4 GB

Runtime1.2 GB

Headroom6.4 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	85.2 tok/s	3303 ms	129K
Chat	C	Runs well	85.2 tok/s	1239 ms	37K
Coding	C	Runs well	85.2 tok/s	2271 ms	71K
RAG	C	Runs well	85.2 tok/s	4129 ms	129K
Reasoning	C	Runs well	85.2 tok/s	2684 ms	71K

How Qwen3.5 9B (9B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	D31
Q3_K_S	3	4.4 GB	Low	D31
NVFP4	4

HuggingFace

huggingface-cli download hf-lmstudio-community--qwen3-5-9b-gguf

Upgrade options

Mac Studio M2 Ultra 128GBBudget pick

C84.5 tok/s decode

~$3,999 MSRP

Mac Studio M1 Ultra 128GBBest value

C80.1 tok/s decode

~$3,999 MSRP