How much VRAM does Qwen3.5 9B need?

Qwen3.5 9B (9B parameters) requires approximately 10.1 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 4000 Ada 20GB can run Qwen3.5 9B with a C grade (Runs well). Expected decode speed: 47.2 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

47.2 tok/s

TTFT

4101 ms

Safe context

32K

Memory

10.1 GB / 20.0 GB

Weights5.5 GB

KV Cache1.4 GB

Runtime1.2 GB

Headroom2.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	47.2 tok/s	5964 ms	56K
Chat	C	Runs well	47.2 tok/s	2237 ms	17K
Coding	C	Runs well	47.2 tok/s	4101 ms	32K
RAG	C	Runs well	47.2 tok/s	7456 ms	56K
Reasoning	C	Runs well	47.2 tok/s	4846 ms	32K

How Qwen3.5 9B (9B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	D33
Q3_K_S	3	4.4 GB	Low	D34
NVFP4	4

HuggingFace

huggingface-cli download hf-unsloth--qwen3-5-9b-gguf

Upgrade options

RX 7900 XTX 24GBBudget pick

C125.9 tok/s decode

~$999 MSRP

RTX 3090 24GBBest value

C119.3 tok/s decode

~$1,499 MSRP

RTX A5000 24GBNVIDIA upgrade

C97.9 tok/s decode

~$2,500 MSRP

NVIDIA A30 24GBBiggest leap