How much VRAM does Llama 3.3 70B need?

Llama 3.3 70B (70B parameters) requires approximately 59.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Llama 3.3 70B?

The recommended quantization for Llama 3.3 70B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

No, Llama 3.3 70B requires more memory than RTX 6000 Ada 48GB provides.

FWon't run

Too heavy

Using Q4_K_M in Ollama

Capabilities:

Fit status

Too heavy

Decode

16.2 tok/s

TTFT

11960 ms

Safe context

13K

Memory

59.6 GB / 48.0 GB

Weights42.7 GB

KV Cache10.9 GB

Runtime1.2 GB

Headroom4.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	F	Too heavy	18.4 tok/s	15275 ms	22K
Chat	D	Very compromised (needs ~4.9 GB host RAM)	16.7 tok/s	6342 ms	7K
Coding	F	Too heavy	16.2 tok/s	11960 ms	13K
RAG	F	Too heavy	18.4 tok/s	19093 ms	22K
Reasoning	F	Too heavy	18.4 tok/s	12411 ms	13K

How Llama 3.3 70B (70B params) fits at each quantization level on RTX 6000 Ada 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	27.3 GB	Low	C42
Q3_K_SBest for your GPU	3	34.3 GB	Low	C44

Upgrade options

MacBook Pro M3 Max 128GBBudget pick

C5.6 tok/s decode

~$2,499 MSRP

MacBook Pro M4 Max 96GBBest value

C8.1 tok/s decode

~$2,499 MSRP

NVIDIA H100 80GBBiggest leap