... proper benchmarks. The Benchmark I tested fine-tuned Qwen3 models (4B to 32B) against frontier models(Claude, ChatGPT) and base Qwen3 on general tasks, 250 prompts total. All finetuned models were trained with 500 examples, 3 epochs, LoRA rank 16. I used Perplexity to create prompts and judge independently. The observations below are based on Perplexity's evaluation. Customer Support Classification (Qwen3-4B) : The improvement compared to base model was small, but definite. Edge cases where the base model confused ... ... here. Frontier models sometimes scored lower because they were too smart, adding guideline level recommendations instead of extracting what the note actually said. The finetuned model better matched the expected extraction style, correctly distinguishing "yes" for chronic conditions vs

... encapsulation** Generates public/private key pairs and securely encapsulates a shared secret using the recipient's public key (via ML-KEM-768). The recipient recovers the exact same shared secret using their private key. Keys are tied to short temporal epochs (5-minute duration by default) and automatically rotated when a new epoch