Except Llama 3 8b is a significant improvement over llama 2, which was basically so terrible that there was a whole community building fine tunes that are better than what the multi billion dollar company can do using a much smaller budget. With llama 3 8b things have shifted towards there being much less community fine-tunes that actually beat it. The fact that Mistral AI can still build models that beat it, means the company isn't falling too far behind a significantly better equipped competitor.

What's more irritating is that they decided to do quantization aware training for fp8. int8 quantization results in an imperceptible loss of quality that is difficult to pick up in benchmarks. They should have gone for something more aggressive like 4-bit, where quantization leads to a significant loss in quality.