Llama 3.1 Family — Local AI Model by Meta

作者： Jakub Rusinowski · 最后更新： 2024年7月23日

Superseded model. Llama 3.1 Family has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point. View Llama 4 →

消费级硬件开源权重的领军者。Llama 3.1拥有高达128k的上下文窗口，在众多基准测试中媲美GPT-4o。

Licence

LicenceWhat it permitsApplies to
Llama CommunityCommercial use permitted
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.		Llama 3.1 8B Instruct

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).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买，LLM Configurator 可能会获得佣金，而你无需支付任何额外费用。作为亚马逊联盟成员（Amazon Associate），LLM Configurator 会从符合条件的购买中获得收益。
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
2026年价格波动较大——请以当前商品页价格为准。
在亚马逊查看价格

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?