How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 10.5 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 Pro M3 Pro 36GB can run Llama 2 7B Chat with a C grade (Runs well). Expected decode speed: 22.8 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

22.8 tok/s

TTFT

8479 ms

Safe context

40K

Memory

10.5 GB / 25.9 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom3.9 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	25.6 tok/s	10981 ms	72K
Chat	C	Runs well	25.6 tok/s	4118 ms	20K
Coding	C	Runs well	22.8 tok/s	8479 ms	40K
RAG	C	Runs well	25.6 tok/s	13726 ms	72K
Reasoning	C	Runs well	25.6 tok/s	8922 ms	40K

How Llama 2 7B Chat (7B params) fits at each quantization level on MacBook Pro M3 Pro 36GB (25.9 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	D32
Q3_K_S	3	3.4 GB	Low	D32
NVFP4	4

Upgrade options

RTX 5090 32GBBudget pick

C281.2 tok/s decode

~$1,999 MSRP

MacBook Pro M4 Max 48GBBest value

C80.6 tok/s decode

~$2,499 MSRP

Mac Studio M1 Ultra 64GBApple upgrade