How much VRAM does Qwen3-VL 30B A3B Instruct need?

Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 23.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-VL 30B A3B Instruct?

The recommended quantization for Qwen3-VL 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, RTX 3090 24GB can run Qwen3-VL 30B A3B Instruct with a C grade (Runs with offload). Expected decode speed: 96.9 tok/s.

CUsable

Runs with offload

Using Q4_K_M in vLLM

Capabilities:

Fit status

Runs with offload

Decode

96.9 tok/s

TTFT

1998 ms

Safe context

16K

Memory

23.9 GB / 24.0 GB

Weights18.3 GB

KV Cache0.8 GB

Runtime2.4 GB

Headroom2.4 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs with offload (needs ~0 GB host RAM)	94.1 tok/s	2993 ms	32K
Chat	C	Runs with offload	94.2 tok/s	1121 ms	8K
Coding	C	Runs with offload	96.9 tok/s	1998 ms	16K
RAG	C	Runs with offload (needs ~0 GB host RAM)	94.1 tok/s	3741 ms	32K
Reasoning	C	Runs with offload	94.2 tok/s	2428 ms

How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on RTX 3090 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	11.7 GB	Low	D40
Q3_K_S	3	14.7 GB	Low	C43
NVFP4Best for your GPU

HuggingFace

huggingface-cli download qwen-3-vl-30b-a3b

Upgrade options

RTX 5090 32GBBudget pick

B172.7 tok/s decode

~$1,999 MSRP

MacBook Pro M4 Max 48GBBest value

B49.5 tok/s decode

~$2,499 MSRP

AMD Instinct MI100 32GBBiggest leap