About Llama 3.1 8B
Llama 3.1 8B is Meta's 8.03B-parameter model released in July 2024, with a 128K-token context window. It uses a classic dense-attention design whose KV cache grows linearly with context: its KV cache is about 1.1 GB at an 8K context, 17.2 GB at 128K, and 17.2 GB at the full 128K window (FP16 cache).
For most people Q4_K_M is the sweet spot — the most popular quality/size trade-off — while Q8 is near-lossless if you have the memory. Totals above include the KV cache and a realistic framework overhead, so they are what you should expect to see in practice rather than just the download size. Weight sizes are calibrated against real GGUF files — see themethodology.
Frequently asked questions
How much VRAM does Llama 3.1 8B need?
At Q4_K_M with an 8K context, Llama 3.1 8B needs about 8 GB (weights 5 GB + KV cache + overhead). The smallest common hardware that fits is a RTX 3060 12GB.
Can an RTX 4090 (24GB) run Llama 3.1 8B?
Yes. An RTX 4090's 24 GB runs Llama 3.1 8B at FP16 / BF16 (about 20 GB at 8K context) — at full FP16 precision.
Can a Mac run Llama 3.1 8B?
Yes — Apple Silicon with 16 GB of unified memory or more (macOS lets the GPU use ~75% of it, ~12 GB) runs Llama 3.1 8B at Q4_K_M.
Related
VRAM calculator for any model ·Token counter
Last updated 2026-08-03. Architecture figures from the model's published config.json; see themethodology.