DiagnosticIQ: leaderboard
Monitoring complex industrial assets relies on engineer-authored symbolic rules that trigger based on sensor conditions and prompt technicians to perform corrective actions. The bottleneck is not detection but response: translating rules into maintenance steps requires asset-specific knowledge gained through years of practice. We investigate whether LLMs can serve as decision support for this rule
Metric: Macro % D.IQ (self-reported). Source: benchmarklist.com. Saturation forecast: Around June 2027. 33 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Opus 4.6 | 73.59 | #63 |
| 2 | GPT-5.4 | 73.27 | #79 |
| 3 | Gemini 3.1 Pro (Preview) | 72.74 | #58 |
| 4 | Claude 3.7 Sonnet | 70.61 | #249 |
| 5 | Qwen 3.6 35B A3B | 69.9 | #226 |
| 6 | DeepSeek V3 | 67.02 | #321 |
| 7 | GPT-5 | 65.89 | #98 |
| 8 | O1 | 65.41 | #183 |
| 9 | Gemma 4 31B | 65.06 | #200 |
| 10 | Claude Sonnet 4.6 | 64.84 | #90 |
| 11 | Llama 4 Maverick | 63.29 | #464 |
| 12 | Gemma 4 26B | 63.2 | #292 |
| 13 | Mistral Large | 63.15 | #710 |
| 14 | Claude Sonnet 4 | 62.52 | #199 |
| 15 | Llama 3.3 70B Instruct | 61.67 | #534 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=diagnosticiq · How It Works · Data refreshed daily, snapshot 2026-10-20.