Meta Releases Llama 3 70B: Open-Source Alternative to GPT-4

The News: Meta released Llama 3 70B, reporting 82.0 on MMLU against GPT-4's 86.4. That is a much narrower gap than Llama 2 managed.

Performance Comparison:

Treat any single benchmark with caution: scores vary with prompting and evaluation setup, so test on your own tasks.

Verdict: Llama 3 70B competitive for most tasks, GPT-4 still better for complex reasoning.

Cost Economics:

GPT-4 Turbo (API):

• Cost: £0.01/1K input, £0.03/1K output
• Cost scales directly with volume

Llama 3 70B (self-hosted on AWS):

• Compute: GPU instances with enough memory to serve a 70B model (quantisation lowers the requirement)
• Setup/maintenance: ongoing DevOps time
• Total: largely fixed, whatever the volume

Breakeven: depends on your volume, instance choice and engineering costs. Work it out with your own numbers.

Low volume: Use the GPT-4 API (cheaper, no ops overhead)

High, sustained volume: Self-hosting Llama 3 70B can win, because costs don't scale with volume

When to Use Llama 3 70B:

✅ High, sustained query volume

✅ Data sovereignty requirements (can't send to third parties)

✅ Offline deployment needed

✅ Cost predictability (fixed cost vs variable API)

❌ Low volume: API cheaper

❌ No ML Ops team: Managing self-hosted models requires expertise

❌ Need cutting-edge performance: GPT-4 still ahead

Open-source opportunity: Fine-tune Llama 3 70B on domain data, potentially match or exceed GPT-4 for specific use cases (legal, medical, finance).

Sources:

• Meta AI Llama 3 Announcement

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