How much VRAM does Llama 3.1 70B need?

Llama 3.1 70B (70B parameters) requires approximately 68.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Llama 3.1 70B?

The recommended quantization for Llama 3.1 70B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, MacBook Pro M3 Max 128GB can run Llama 3.1 70B with a C grade (Runs well). Expected decode speed: 6.1 tok/s.

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

6.1 tok/s

TTFT

31795 ms

Safe context

21K

Memory

68.7 GB / 92.2 GB

Weights42.7 GB

KV Cache10.9 GB

Runtime1.2 GB

Headroom13.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Tight fit	5.6 tok/s	50101 ms	37K
Chat	C	Runs well	5.6 tok/s	18788 ms	12K
Coding	C	Runs well	6.1 tok/s	31795 ms	21K
RAG	C	Tight fit	5.6 tok/s	62627 ms	37K
Reasoning	C	Runs well	5.6 tok/s	40707 ms	21K

How Llama 3.1 70B (70B params) fits at each quantization level on MacBook Pro M3 Max 128GB (92.2 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	27.3 GB	Low	D36
Q3_K_S	3	34.3 GB	Low	D37
NVFP4	4

Ollama

ollama run llama-3.1-70b

HuggingFace

huggingface-cli download llama-3.1-70b

Upgrade options

AMD Instinct MI250X 128GBBudget pick

C58.5 tok/s decode

~$15,000 MSRP

AMD Instinct MI300X 192GBBest value

C96.8 tok/s decode

~$15,000 MSRP

NVIDIA GH200 96GBBiggest leap