How much VRAM does Meta-Llama-3.2-3B need?

Q4_K_M is exactly 2,019,373,888 bytes (1.88 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

meta-llama · text

Meta-Llama-3.2-3B

meta-llama/Meta-Llama-3.2-3B

Meta-Llama-3.2-3B at Q4_K_M is exactly 2,019,373,888 bytes (1.88 GiB / 2.02 GB) — an effective 5.028 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)

Parameters

3.2B

Architecture

llama

Context

—

native (config.json)

License

llama3

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q4_K_M	1.88 GiB	2,019,373,888	5.028	—	NousResearch
Q4_K_M	1.88 GiB	2,019,377,664	5.028	—	Bllossom
Q5_K_M	2.16 GiB	2,322,150,208	5.782	—	NousResearch
Q6_K	2.46 GiB	2,643,850,048	6.583	—	NousResearch
Q8_0	3.19 GiB	3,421,895,488	8.521	—	NousResearch

Compare with

same modality, comparable size

vs gemma-4-E4B-it vs Qwen3-4B vs Qwen3-8B vs HyperCLOVAX-SEED-Text-Instruct-1.5B vs Llama-3.2-1B-Instruct vs Qwen3-VL-8B-Instruct-abliterated-v1 All alternatives →Will it fit on my card? →

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 1.68 GiB. The real file is 1.88 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

Architecture unavailable — this repository is gated and no ungated mirror was found. Exact file sizes above are still authoritative; only the KV math needs the config.

Questions people ask

How much VRAM does Meta-Llama-3.2-3B need?: Q4_K_M is exactly 2,019,373,888 bytes (1.88 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Meta-Llama-3.2-3B should I use?: Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.