First test run results on 1x NVIDIA A100 (80GB): Training Efficiency: Time: 30 minutes. Batch Size: 131,072 tokens per step. Throughput: ~30,000 tokens/sec. Convergence: Loss 12.8 ➔ 3.39 (378 steps). Depth: 24 data processing cycles. Parameters: 17,146,027. Vocabulary Size: 1,024 Archive Size (.ptz): 4.124 MB (4x margin relative to the competition limit). Compression Degradation: 0.78% (Delta).

Accuracy remains nearly unchanged after converting to the final compact format. Final Eval: val_loss: 10.26935238 | val_bpb: 6.00998162. Note: These results are from a raw baseline run without any hyperparameter tuning. Expect even more aggressive performance in the upcoming cycles. ꙮ 🚀