MaziyarPanahi / text-generation updated 2 years ago

Meta-Llama-3-8B-Instruct-GGUF

- Model creator: meta-llama - Original model: meta-llama/Meta-Llama-3-8B-Instruct

Params
Context
Downloads 30d
180 K
Likes
103
Licence: unknown Not gated GGUF 1 languages View on Hugging Face ↗

Download history

daily snapshots · 34 days
▲ 8 K in the last 30 days (4.4%)
191 K180 K
Aug 19Aug 30Sep 10Sep 21

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
Meta-Llama-3-8B-Instruct.IQ1_S.gguf IQ1_S 2.0 GB 2.7 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.IQ1_M.gguf IQ1_M 2.2 GB 2.9 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.IQ2_XS.gguf IQ2_XS 2.6 GB 3.4 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.Q2_K.gguf Q2_K 3.2 GB 4.0 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.IQ3_XS.gguf IQ3_XS 3.5 GB 4.4 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.Q3_K_M.gguf Q3_K_M 4.0 GB 4.9 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.Q3_K_L.gguf Q3_K_L 4.3 GB 5.3 GB ✅ Runs comfortably
Meta-Llama-3-8B-Instruct.IQ4_XS.gguf IQ4_XS 4.4 GB 5.4 GB ✅ Runs comfortably
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · IQ1_M
$ ollama run meta-llama-3-8b-instruct-gguf

# pin the quantization explicitly
$ ollama run meta-llama-3-8b-instruct-gguf-iq1_m
est. VRAM 2.9 GBon RTX 4090 · 24 GBJSON API →

Specifications

First seen on the Hub
2024-04-18
Base model
Meta-Llama-3-8B-Instruct
Training datasets
undisclosed
Added to our catalog
2026-08-19

Family

Base model and the most-downloaded derivatives in the catalog.

Compare with any text-generation model