How much VRAM does DeepSeek LLM 67B need?

DeepSeek LLM 67B (67B parameters) requires approximately 67.6 GB of memory with Q4_K_M quantization.

What is the best quantization for DeepSeek LLM 67B?

The recommended quantization for DeepSeek LLM 67B is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, MacBook Pro M3 Max 128GB can run DeepSeek LLM 67B with a C grade (Runs well). Expected decode speed: 6.4 tok/s.

CUsable

Runs well

Using Q4_K_M in vLLM

Capabilities:

Fit status

Runs well

Decode

6.4 tok/s

TTFT

30432 ms

Safe context

Memory

67.6 GB / 92.2 GB

Weights40.9 GB

KV Cache10.5 GB

Runtime2.4 GB

Headroom13.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Tight fit	6.4 tok/s	44265 ms	4K
Chat	C	Runs well	6.4 tok/s	16600 ms	4K
Coding	C	Runs well	6.4 tok/s	30432 ms	4K
RAG	C	Tight fit	6.4 tok/s	55332 ms	4K
Reasoning	C	Runs well	6.4 tok/s	35966 ms	4K

How DeepSeek LLM 67B (67B params) fits at each quantization level on MacBook Pro M3 Max 128GB (92.2 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	26.1 GB	Low	D35
Q3_K_S	3	32.8 GB	Low	D37
NVFP4	4

Ollama

ollama run deepseek-llm-67b

HuggingFace

huggingface-cli download deepseek-llm-67b

Upgrade options

AMD Instinct MI250X 128GBBudget pick

C61.1 tok/s decode

~$15,000 MSRP

AMD Instinct MI300X 192GBBest value

C101.1 tok/s decode

~$15,000 MSRP

NVIDIA GH200 96GBBiggest leap