Llama 3.3 — Local AI Model by Meta

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

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

Meta's latest flagship model. Llama 3.3 70B delivers state-of-the-art performance, matching the massive 405B model in many benchmarks while remaining efficient enough for high-end local setups.

Hardware Requirements

Llama 3.3 70B Instruct Min 43 GB VRAM · Q2_K_XS (Tight) · 128,000 ctx · ollama run llama3.3

Recommended GPU

The cheapest GPU that runs Llama 3.3 locally (min 43 GB VRAM) is the AMD Ryzen AI Max+ 395 (96 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.

GMKtec EVO-X2 (Ryzen AI Max+ 395, 128GB)

Sugerowana cena premierowa: $2,349

Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.

Sprawdź cenę na Amazon

How to Run Locally

Install Ollama then run: ollama run llama3.3

Minimum VRAM: 43 GB. For best results use Q4_K_M quantization.

Llama 3.3 — Frequently Asked Questions

How much VRAM does Llama 3.3 need?

Llama 3.3 needs about 43 GB VRAM at Q2_K_XS (Tight) quantization for its smallest variant. Variants: Llama 3.3 70B Instruct (43 GB, Q2_K_XS (Tight)). On Apple Silicon, unified memory counts toward this requirement.

Can I run Llama 3.3 on an RTX 4090 (24 GB)?

Llama 3.3's smallest variant needs about 43 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.

What quantization should I use for Llama 3.3?

Q4_K_M is the best balance of quality and VRAM for Llama 3.3 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 3.3 with Ollama?

Install Ollama, then run: ollama run llama3.3. This downloads Llama 3.3 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.