About Llama 3.3 70B
Llama 3.3 70B is Meta's 70.6B-parameter model released in December 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 2.7 GB at an 8K context, 42.9 GB at 128K, and 42.9 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 3.3 70B need?
At Q4_K_M with an 8K context, Llama 3.3 70B needs about 51 GB (weights 43 GB + KV cache + overhead). The smallest common hardware that fits is a A100 80GB.
Can an RTX 4090 (24GB) run Llama 3.3 70B?
Not fully in VRAM. Llama 3.3 70B needs about 51 GB even at Q4_K_M, so a 24 GB card would have to offload layers to system RAM at a large speed penalty.
Can a Mac run Llama 3.3 70B?
Yes — Apple Silicon with 96 GB of unified memory or more (macOS lets the GPU use ~75% of it, ~72 GB) runs Llama 3.3 70B 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.