How much VRAM does Llama 3.2 3B Instruct need?

Llama 3.2 3B Instruct (3B parameters) requires approximately 12.2 GB of memory with Q5_K_M quantization.

What is the best quantization for Llama 3.2 3B Instruct?

The recommended quantization for Llama 3.2 3B Instruct is Q5_K_M, which balances quality and memory efficiency.

Can it run?

Yes, NVIDIA A800 80GB can run Llama 3.2 3B Instruct with a C grade (Runs well). Expected decode speed: 657.9 tok/s.

CUsable

Runs well

Using Q5_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

657.9 tok/s

TTFT

350 ms

Safe context

105K

Memory

12.2 GB / 80.0 GB

Weights2.2 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom8.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	712.7 tok/s	395 ms	208K
Chat	C	Runs well	712.7 tok/s	350 ms	53K
Coding	C	Runs well	657.9 tok/s	350 ms	105K
RAG	C	Runs well	712.7 tok/s	494 ms	208K
Reasoning	C	Runs well	712.7 tok/s	350 ms	105K

How Llama 3.2 3B Instruct (3B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.2 GB	Low	D30
Q3_K_S	3	1.5 GB	Low	D30
NVFP4	4

HuggingFace

huggingface-cli download hf-bartowski--llama-3-2-3b-instruct-gguf

Upgrade options

MacBook Pro M3 Max 128GBBudget pick

C113.3 tok/s decode

~$2,499 MSRP

Mac Studio M1 Ultra 128GBBest value

C207.8 tok/s decode

~$3,999 MSRP