SAGE (Service Agent) - Conversational Quality: leaderboard

Metric: Conversational Quality Score (0-100): weighted judge ratings of linguistic quality, anthropomorphism, content utility, user satisfaction and instruction compliance, averaged over three judges, averaged over the six scenarios, over SAGE customer-service dialogues: standard operating procedures formalized as dialogue graphs, an adversarial simulated user with varied intents and personas, turns 1, 5, 10, 15 and the final turn scored; three unnamed judge LLMs (majority vote and mean) plus a deterministic rule engine produce the reference; closed models through their APIs, open models served with vLLM; 0-100 scale; higher is better. Source: arxiv.org. Saturation forecast: Around May 2027. 27 models tracked.

Top models

Interactive version: theaggregate.ai/benchmark?slug=sage-service-agent-conversational-quality · How It Works · Data refreshed daily, snapshot 2026-10-07.