How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 10.0 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 M4 32GB can run Llama 2 7B Chat with a C grade (Runs well). Expected decode speed: 18.3 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

18.3 tok/s

TTFT

10598 ms

Safe context

37K

Memory

10.0 GB / 23.0 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom3.5 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	20.2 tok/s	13917 ms	66K
Chat	C	Runs well	20.2 tok/s	5219 ms	19K
Coding	C	Runs well	18.3 tok/s	10598 ms	37K
RAG	C	Runs well	20.2 tok/s	17396 ms	66K
Reasoning	C	Runs well	20.2 tok/s	11308 ms	37K

How Llama 2 7B Chat (7B params) fits at each quantization level on MacBook Pro M4 32GB (23.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	D32
Q3_K_S	3	3.4 GB	Low	D33
NVFP4	4

Upgrade options

RX 7900 XTX 24GBBudget pick

C161.9 tok/s decode

~$999 MSRP

RTX 3090 24GBBest value

C153.4 tok/s decode

~$1,499 MSRP

MacBook Pro M4 Max 36GBApple upgrade