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Learn · Popular Open Source Models · Meta Llama & Mistral Foundations

Llama 3.1 & 3.3 (8B, 70B)

In plain English

Meta's Llama 3 series is the universal baseline of open-source AI. Almost every local app, tool, and fine-tuning tutorial is built to support Llama 3 first! 🦙

What is actually going on

Llama 3.1/3.3 features a standard Grouped-Query Attention (GQA) architecture with 128k token context windows trained on 15+ trillion tokens. The 8B model fits in ~5.5GB (Q4_K_M), running on nearly any laptop. The 70B model requires ~40GB (Q4_K_M), serving as the high-accuracy baseline for enterprise local inference.

Why it matters

Llama 3 has the widest ecosystem support: every quantization library, fine-tuning script, and inference engine tests against Llama 3 first.

Another way to think about it

The Toyota Corolla of local AI: reliable, universal parts everywhere, and runs smoothly in any garage. 🚗

Check yourself

  1. What is the context window length supported by Llama 3.1 and 3.3?

    • 4k tokens
    • 8k tokens
    • 32k tokens
    • 128k tokens
    Show answer

    128k tokens — Llama 3.1 and 3.3 support a native 128k token context window.

Terms from this lesson

Grouped-Query Attention (GQA)Local InferenceQuantizationAttention