How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 13.0 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, NVIDIA A16 64GB can run Llama 2 7B Chat with a C grade (Runs well). Expected decode speed: 101.2 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

101.2 tok/s

TTFT

1914 ms

Safe context

79K

Memory

13.0 GB / 64.0 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom6.4 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	109.6 tok/s	2569 ms	146K
Chat	C	Runs well	109.6 tok/s	963 ms	40K
Coding	C	Runs well	101.2 tok/s	1914 ms	79K
RAG	C	Runs well	109.6 tok/s	3212 ms	146K
Reasoning	C	Runs well	109.6 tok/s	2088 ms	79K

How Llama 2 7B Chat (7B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	D30
Q3_K_S	3	3.4 GB	Low	D31
NVFP4	4

Upgrade options

MacBook Pro M4 Max 96GBBudget pick

C80.6 tok/s decode

~$2,499 MSRP

Mac Studio M1 Ultra 128GBBest value

C103 tok/s decode

~$3,999 MSRP