Meta AI
8.03 Billion Parameters (Dense GQA)
Meta LLaMA 3.1 8B Instruct VRAM Requirements Guide
The most widely deployed open-weights 8B model. Runs comfortably on 8GB and 12GB budget consumer GPUs with up to 128k context.
4-Bit (Q4_K_M) - Recommended
7.64 GB
>98% perplexity retention. Standard Ollama/llama.cpp quantization.
8-Bit (Q8_0) - Near Lossless
11.52 GB
Virtually identical to FP16 (~99.9% fidelity). Demands high-capacity VRAM.
16-Bit (FP16 / BF16) - Full
19.40 GB
Uncompressed weights. Requires multi-GPU clusters or datacenter cards.
Recommended Hardware Sweet Spot
NVIDIA RTX 3060 (12GB) or RTX 4060 (8GB)
Provides sufficient headroom for weights, 8k+ context KV-cache, and CUDA runtime buffers without Out-Of-Memory (OOM) crashes.
Run Meta LLaMA 3.1 8B Instruct Locally
Ollama:
ollama run llama3.1:8b-instruct-q4_K_MvLLM:
vllm serve meta-llama/Meta-Llama-3.1-8B-Instruct --max-model-len 8192 --gpu-memory-utilization 0.95Test Custom Hardware & Context Windows
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