How much VRAM does Llama 2 7B Chat need?

Llama 2 7B Chat (7B parameters) requires approximately 14.6 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 H100 80GB can run Llama 2 7B Chat with a C grade (Runs well). Expected decode speed: 564.9 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

564.9 tok/s

TTFT

350 ms

Safe context

88K

Memory

14.6 GB / 80.0 GB

Weights4.3 GB

KV Cache1.1 GB

Runtime1.2 GB

Headroom8.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	564.9 tok/s	499 ms	163K
Chat	C	Runs well	564.9 tok/s	350 ms	45K
Coding	C	Runs well	564.9 tok/s	350 ms	88K
RAG	C	Runs well	564.9 tok/s	623 ms	163K
Reasoning	C	Runs well	564.9 tok/s	405 ms	88K

How Llama 2 7B Chat (7B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).

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

Upgrade options

Mac Studio M1 Ultra 128GBBudget pick

C103 tok/s decode

~$3,999 MSRP

Mac Studio M2 Ultra 128GBBest value

C108.7 tok/s decode

~$3,999 MSRP