How much VRAM does Qwen3.5 27B need?

Qwen3.5 27B (27B parameters) requires approximately 24.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3.5 27B?

The recommended quantization for Qwen3.5 27B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, NVIDIA A30 24GB can run Qwen3.5 27B with a C grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 43.7 tok/s.

CUsable

Runs with offload (needs ~0.2 GB host RAM)

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs with offload (needs ~0.2 GB host RAM)

Decode

43.7 tok/s

TTFT

4426 ms

Safe context

16K

Memory

24.3 GB / 24.0 GB

Weights16.5 GB

KV Cache4.2 GB

Runtime1.2 GB

Headroom2.4 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	D	Very compromised (needs ~2.6 GB host RAM)	38.2 tok/s	7363 ms	27K
Chat	C	Tight fit	44.2 tok/s	2390 ms	9K
Coding	C	Runs with offload (needs ~0.2 GB host RAM)	43.7 tok/s	4426 ms	16K
RAG	D	Very compromised (needs ~2.6 GB host RAM)	38.2 tok/s	9203 ms	27K
Reasoning	C	Runs with offload (needs ~0.2 GB host RAM)	43.7 tok/s

How Qwen3.5 27B (27B params) fits at each quantization level on NVIDIA A30 24GB (24.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	10.5 GB	Low	D39
Q3_K_S	3	13.2 GB	Low	C41
NVFP4	4

HuggingFace

huggingface-cli download hf-unsloth--qwen3-5-27b-gguf

Upgrade options

RTX 5090 32GBBudget pick

B72.9 tok/s decode

~$1,999 MSRP

MacBook Pro M4 Max 48GBBest value

C20.9 tok/s decode

~$2,499 MSRP

NVIDIA A100 40GBBiggest leap

B79.3 tok/s decode

~$10,000 MSRP