Llama 3.1 Family — Local AI Model by Meta

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

The reigning champion of open weights for consumer hardware. Llama 3.1 features a massive 128k context window and rivals GPT-4o in many benchmarks.

Hardware Requirements

Llama 3.1 8B InstructMin 6 GB VRAM · Q4_K_M · 128,000 ctx · ollama run llama3.1

Recommended GPU

The cheapest GPU that runs Llama 3.1 Family locally (min 6 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 llama3.1

Minimum VRAM: 6 GB. For best results use Q4_K_M quantization.

Download Llama 3.1 Family — GGUF Quantizations

Pick a quantization and open it in LM Studio, Ollama, or Jan, or download the raw .gguf file directly. Quant list and sizes resolved from Hugging Face.

Llama 3.1 8B Instruct — GGUF quants · bartowski/Meta-Llama-3.1-8B-Instruct-GGUF

QuantSizeDownload (.gguf)
Q3_K_M3.41 GB (est.)Meta-Llama-3.1-8B-Instruct-Q3_K_M.gguf
Q4_K_M4.83 GB (est.)Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf
Q5_K_M5.67 GB (est.)Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf
Q6_K6.56 GB (est.)Meta-Llama-3.1-8B-Instruct-Q6_K.gguf
Q8_08.50 GB (est.)Meta-Llama-3.1-8B-Instruct-Q8_0.gguf

Download in LM Studio: lms get bartowski/Meta-Llama-3.1-8B-Instruct-GGUF

Want this model on your phone? You can run it on your desktop with LM Studio and chat from your iPhone or iPad over an encrypted link — see Run LM Studio Models on Your Phone (LM Link).

Llama 3.1 Family — Frequently Asked Questions

How much VRAM does Llama 3.1 Family need?

Llama 3.1 Family needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Llama 3.1 8B Instruct (6 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Llama 3.1 Family on an RTX 4090 (24 GB)?

Yes — Llama 3.1 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 3.1 Family?

Q4_K_M is the best balance of quality and VRAM for Llama 3.1 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 3.1 Family with Ollama?

Install Ollama, then run: ollama run llama3.1. This downloads Llama 3.1 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.

Can I Run Llama 3.1 Family on My GPU?