How much VRAM does Llama 3.3 70B need?

Llama 3.3 70B (70B parameters) requires approximately 61.2 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?

Yes, AMD Instinct MI210 64GB can run Llama 3.3 70B with a C grade (Runs with offload). Expected decode speed: 27.6 tok/s.

CUsable

Runs with offload

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs with offload

Decode

27.6 tok/s

TTFT

7009 ms

Safe context

17K

Memory

61.2 GB / 64.0 GB

Weights42.7 GB

KV Cache10.9 GB

Runtime1.2 GB

Headroom6.4 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	D	Very compromised (needs ~4.8 GB host RAM)	23.6 tok/s	11945 ms	28K
Chat	C	Tight fit	26.1 tok/s	4048 ms	9K
Coding	C	Runs with offload	27.6 tok/s	7009 ms	17K
RAG	D	Very compromised (needs ~4.8 GB host RAM)	23.6 tok/s	14932 ms	28K
Reasoning	C	Runs with offload	26.1 tok/s	8771 ms

How Llama 3.3 70B (70B params) fits at each quantization level on AMD Instinct MI210 64GB (64.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	27.3 GB	Low	D39
Q3_K_S	3	34.3 GB	Low	C41
NVFP4	4

Ollama

ollama run llama-3.3-70b

HuggingFace

huggingface-cli download llama-3.3-70b

Upgrade options

Mac Studio M2 Ultra 128GBBudget pick

C10.9 tok/s decode

~$3,999 MSRP

Mac Studio M1 Ultra 128GBBest value

C10.3 tok/s decode

~$3,999 MSRP

NVIDIA H100 80GBBiggest leap