A 70ms Local NLI Judge Hits 0.596 Pearson r With Groq Llama 3.3 70B on DSPy Reward Scoring

TL;DR semantic_reward is a drop-in DSPy reward function powered by a local quantized NLI cross-encoder — no API call, no key, deterministic, ~70ms per evaluation on CPU. On 50 paired customer-support examples , semantix reaches Pearson r = 0.596 with Groq Llama 3.3 70B, and Cohen's kappa 0.633 at threshold 0.3 (substantial agreement), at ~11× lower latency and $0.13 cheaper per 1k calls . Full reproducibility: code, dataset, raw CSVs at github.com/labrat-akhona/semantix-ai/benchmarks . Why anoth