How much VRAM does Qwen3.5 9B need?

Qwen3.5 9B (9B parameters) requires approximately 12.1 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, NVIDIA A100 40GB can run Qwen3.5 9B with a C grade (Runs well). Expected decode speed: 203.9 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

203.9 tok/s

TTFT

949 ms

Safe context

53K

Memory

12.1 GB / 40.0 GB

Weights5.5 GB

KV Cache1.4 GB

Runtime1.2 GB

Headroom4.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	237.9 tok/s	1184 ms	95K
Chat	C	Runs well	237.9 tok/s	444 ms	28K
Coding	C	Runs well	203.9 tok/s	949 ms	53K
RAG	C	Runs well	237.9 tok/s	1479 ms	95K
Reasoning	C	Runs well	237.9 tok/s	962 ms	53K

How Qwen3.5 9B (9B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	D31
Q3_K_S	3	4.4 GB	Low	D32
NVFP4	4

HuggingFace

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

Upgrade options

Mac Studio M2 Ultra 64GBBudget pick

C84.5 tok/s decode

~$3,999 MSRP

Mac Studio M1 Ultra 64GBBest value

C80.1 tok/s decode

~$3,999 MSRP