How much VRAM does Qwen3.5 9B need?

Qwen3.5 9B (9B parameters) requires approximately 9.7 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, RTX 4060 Ti 16GB can run Qwen3.5 9B with a C grade (Runs well). Expected decode speed: 37.8 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

37.8 tok/s

TTFT

5126 ms

Safe context

26K

Memory

9.7 GB / 16.0 GB

Weights5.5 GB

KV Cache1.4 GB

Runtime1.2 GB

Headroom1.6 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	38.3 tok/s	7353 ms	46K
Chat	C	Runs well	38.3 tok/s	2758 ms	14K
Coding	C	Runs well	37.8 tok/s	5126 ms	26K
RAG	C	Runs well	38.3 tok/s	9192 ms	46K
Reasoning	C	Runs well	38.3 tok/s	5975 ms	26K

How Qwen3.5 9B (9B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	D34
Q3_K_S	3	4.4 GB	Low	D35
NVFP4	4

HuggingFace

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

Upgrade options

RX 7900 XT 20GBBudget pick

C87.4 tok/s decode

~$899 MSRP

MacBook Pro M4 Pro 24GBBest value

C38.3 tok/s decode

~$1,999 MSRP

RTX A4500 20GBBiggest leap