How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 8.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Llama 2 7B Chat?

The recommended quantization for Llama 2 7B Chat is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, MacBook Air M2 16GB can run Llama 2 7B Chat with a C grade (Runs well). Expected decode speed: 15.2 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

15.2 tok/s

TTFT

12718 ms

Safe context

22K

Memory

8.3 GB / 11.5 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom1.7 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	15.2 tok/s	18499 ms	39K
Chat	C	Runs well	15.2 tok/s	6937 ms	12K
Coding	C	Runs well	15.2 tok/s	12718 ms	22K
RAG	C	Runs well	15.2 tok/s	23124 ms	39K
Reasoning	C	Runs well	15.2 tok/s	15030 ms	22K

How Llama 2 7B Chat (7B params) fits at each quantization level on MacBook Air M2 16GB (11.5 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	D35
Q3_K_S	3	3.4 GB	Low	D36
NVFP4	4

Upgrade options

Intel Arc B580 12GBBudget pick

C51.3 tok/s decode

~$249 MSRP

RTX 3060 12GBBest value

C55.6 tok/s decode

~$329 MSRP

RTX 3080 12GBBiggest leap

B162.3 tok/s decode

~$799 MSRP

MacBook Pro M3 Pro 18GB