SAGE (Service Agent) - Property Service: leaderboard
Metric: Overall Assessment Score (0-100), 0.8 x logical compliance + 0.2 conversational quality, in the Property Service scenario (property service requests such as repairs and noise complaints), 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 January 2027. 27 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Sonnet 4.5 | 75.07 |
| 2 | Gemini 3 Pro (Preview) | 73.65 |
| 3 | Claude Opus 4.5 | 73.25 |
| 4 | Kimi K2.5 | 71.84 |
| 5 | Gemini 3 Flash (Preview) | 71.62 |
| 6 | DeepSeek V3.2 | 70.71 |
| 7 | DeepSeek R1 | 70.58 |
| 8 | GLM-4.7 | 69.64 |
| 9 | Gemini 2.5 Pro | 69.6 |
| 10 | Seed 1.8 | 69.03 |
| 11 | DeepSeek V3 | 67.57 |
| 12 | Qwen 3 32B | 66.71 |
| 13 | Qwen 2.5 72B Instruct | 65.78 |
| 14 | GPT-4.1 | 65.46 |
| 15 | Qwen 3 14B | 64.81 |
Interactive version: theaggregate.ai/benchmark?slug=sage-service-agent-property-service · How It Works · Data refreshed daily, snapshot 2026-10-07.