Question 1

How much VRAM do I need to run a 70B model?

Accepted Answer

A 70B model at Q4 quantization typically requires around 35-40 GB of VRAM. You can run it on a multi-GPU setup, a Mac with 48GB+ unified memory, or a cloud GPU instance.

Question 2

Can I run LLMs on a consumer GPU?

Accepted Answer

Yes! Many models like Llama 3.2 3B, Gemma 2 2B, and Phi-3 Mini can run on GPUs with 6-8 GB VRAM using 4-bit quantization. Use LocalOps to find the best match for your hardware.

Question 3

What is quantization and does it affect quality?

Accepted Answer

Quantization reduces model precision (e.g., from FP16 to Q4) to lower VRAM usage. Q4_K_M is the recommended sweet spot, offering ~50% VRAM savings with minimal quality loss.

Format	VRAM Need	Tier
FP16	15.6 GB	Full Precision
Q8_0	7.8 GB	High
Q6_K	6.6 GB	Excellent
Q5_K_M	5.5 GB	Great
Q4_K_M	3.9 GB	Sweet Spot
Q2_K	2.3 GB	Emergency

EXAONE 3.0 7.8B

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