v2.2 · 2026-06-12

Meta Llama 3.1 8B Instruct

llama-3-1-8b-instruct

TEXT-CHAT

Meta Llama 3.1 8B Instruct is a 8.03B text chat model profile for local AI planning. This page records provider, license, context, quantization, hardware-fit estimates, setup hints, source links, and caveats so readers do not choose a model by name alone.

PROVIDER

Meta

FAMILY

llama

MODEL TYPE

text-chat

PARAMETERS

8.03B

MODALITIES

text

ARCHITECTURE

decoder-only Transformer (LlamaForCausalLM) with grouped-query attention

CONTEXT WINDOW

128,000 tokens

TRAINING TOKENS

15.0T

RELEASE DATE

2024-07-23

LICENSE & LINKS

Llama 3.1 Community Licenselicense text

MODEL CARD

huggingface.co/meta-llama/Llama-3.1-8B-Instruct

HUGGING FACE

meta-llama/Llama-3.1-8B-Instruct

GGUF REPOSITORIES

bartowski/Meta-Llama-3.1-8B-Instruct-GGUF community conversion

Community GGUF conversion with Q4_K_M, Q5_K_M and Q8_0 file-size table.

SETUP HINTS

OLLAMA

ollama run llama3.1:8b

LM STUDIO

Search for bartowski/Meta-Llama-3.1-8B-Instruct-GGUF and select Q4_K_M or Q5_K_M.

LLAMA.CPP

llama-server -hf bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M

QUANTIZATION FILE SIZES (GGUF)

Q4_K_M

4.92 GB

Q5_K_M

5.73 GB

Q8_0

8.54 GB

Quantization note: Q4_K_M

RAM / VRAM ESTIMATES

MIN RAM

8 GB

COMFORTABLE RAM

16 GB

MIN VRAM

6 GB

COMFORTABLE VRAM

8 GB

These are conservative local-inference estimates, not official hardware requirements.

HARDWARE FIT

CPU only (no GPU)

yes

8 GB RAM

limited

16 GB RAM

comfortable

32 GB RAM

comfortable

8 GB VRAM

good

12 GB VRAM

comfortable

24 GB VRAM

comfortable

Apple Silicon (unified memory)

comfortable

Hardware fit values are conservative local-inference estimates based on GGUF size plus runtime and KV-cache overhead. Actual requirements depend on context length, quantization, runtime, GPU offload, and other running apps.

BEST FOR

·balanced local general chat

·multilingual assistant use

·tool-calling and lightweight agent workflows

·RAG/chatbot baselines on consumer hardware

AVOID IF

·you need top-tier reasoning quality

·you only have 8 GB system RAM and want long contexts

·you require an Apache-2.0 license

CAVEATS

·RAM and VRAM estimates are conservative local-inference estimates based on GGUF file size plus runtime and KV-cache overhead, not official Meta requirements.

·The Llama license is not Apache-2.0; review the acceptable-use and redistribution terms before commercial catalog use.

SOURCE URLS