How much VRAM does llava llama 3 8b v1 1 need?

llava llama 3 8b v1 1 (8B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.

What is the best quantization for llava llama 3 8b v1 1?

The recommended quantization for llava llama 3 8b v1 1 is Q4_K_M, which balances quality and memory efficiency.

Can it run?

Yes, RTX 4070 Laptop 8GB can run llava llama 3 8b v1 1 with a C grade (Runs with offload). Expected decode speed: 37.3 tok/s.

CUsable

Runs with offload

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs with offload

Decode

37.3 tok/s

TTFT

5196 ms

Safe context

16K

Memory

8.1 GB / 8.0 GB

Weights4.9 GB

KV Cache1.3 GB

Runtime1.2 GB

Headroom0.8 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Very compromised (needs ~0.7 GB host RAM)	34.9 tok/s	8073 ms	27K
Chat	C	Runs with offload	39.9 tok/s	2649 ms	8K
Coding	C	Runs with offload	37.3 tok/s	5196 ms	16K
RAG	C	Very compromised (needs ~0.7 GB host RAM)	34.9 tok/s	10091 ms	27K
Reasoning	C	Runs with offload (needs ~0.1 GB host RAM)	39.3 tok/s	5818 ms

How llava llama 3 8b v1 1 (8B params) fits at each quantization level on RTX 4070 Laptop 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	D38
Q3_K_S	3	3.9 GB	Low	D40
NVFP4	4

Upgrade options

Intel Arc B580 12GBBudget pick

C44.9 tok/s decode

~$249 MSRP

RTX 3060 12GBBest value

B48.7 tok/s decode

~$329 MSRP

RTX 3080 12GBBiggest leap

B142 tok/s decode

~$799 MSRP

RTX 3080 Ti 12GBNVIDIA upgrade

B138.3 tok/s decode

~$1,199 MSRP