How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 9.2 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 M3 24GB 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

30K

Memory

9.2 GB / 17.3 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom2.6 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	15.9 tok/s	17683 ms	54K
Chat	C	Runs well	15.9 tok/s	6631 ms	16K
Coding	C	Runs well	15.2 tok/s	12718 ms	30K
RAG	C	Runs well	15.9 tok/s	22104 ms	54K
Reasoning	C	Runs well	15.2 tok/s	15030 ms	30K

How Llama 2 7B Chat (7B params) fits at each quantization level on MacBook Air M3 24GB (17.3 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	D33
Q3_K_S	3	3.4 GB	Low	D34
NVFP4	4

Upgrade options

RX 7900 XT 20GBBudget pick

C112.4 tok/s decode

~$899 MSRP

RX 7900 XTX 24GBBest value

C161.9 tok/s decode

~$999 MSRP