Llama 3.2 Family — Local AI Model by Meta

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

Meta's multimodal and edge-optimized series. Llama 3.2 introduces vision capabilities (11B and 90B variants) and ultra-compact 1B/3B versions designed to run on smartphones and edge devices. All variants feature a 128k context window.

Hardware Requirements

Llama 3.2 1B Instruct	Min 1 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run llama3.2:1b`
Llama 3.2 3B Instruct	Min 2 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run llama3.2:3b`
Llama 3.2 11B Vision Instruct	Min 8 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run llama3.2-vision:11b`
Llama 3.2 90B Vision Instruct	Min 48 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run llama3.2-vision:90b`

Recommended GPU

The cheapest GPU that runs Llama 3.2 Family locally (min 1 GB VRAM) is the Intel Arc B570 (10 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

Intel Arc B570 10GB

Sugerowana cena premierowa: $219

Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.

Sprawdź cenę na Amazon

How to Run Locally

Install Ollama then run: ollama run llama3.2:1b

Minimum VRAM: 1 GB. For best results use Q4_K_M quantization.

Llama 3.2 Family — Frequently Asked Questions

How much VRAM does Llama 3.2 Family need?

Llama 3.2 Family needs about 1 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Llama 3.2 1B Instruct (1 GB, Q4_K_M); Llama 3.2 3B Instruct (2 GB, Q4_K_M); Llama 3.2 11B Vision Instruct (8 GB, Q4_K_M); Llama 3.2 90B Vision Instruct (48 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Llama 3.2 Family on an RTX 4090 (24 GB)?

Yes — Llama 3.2 Family runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for Llama 3.2 Family?

Q4_K_M is the best balance of quality and VRAM for Llama 3.2 Family in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Llama 3.2 Family with Ollama?

Install Ollama, then run: ollama run llama3.2:1b. This downloads Llama 3.2 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.