Multi-IF: leaderboard
4,501 three-turn instruction-following conversations in 8 languages built from IFEval prompts (Meta, 2024); each turn adds verifiable constraints; average accuracy across turns and languages.
Metric: Average (self-reported). Source: benchmarklist.com. Status: saturation imminent. 15 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | O1 Preview | 87.7 |
| 2 | Ling-3.0-flash | 87.7 |
| 3 | Llama 3.1 405B | 85.4 |
| 4 | O1 Mini | 85.3 |
| 5 | GPT-4o | 84.3 |
| 6 | Qwen 2.5 72B | 83.7 |
| 7 | Llama 3.1 70B | 82.6 |
| 8 | Claude 3.5 Sonnet | 81.7 |
| 9 | GPT-4 | 81.5 |
| 10 | Mistral Large 2 (Jul) | 80.5 |
| 11 | Claude 3 Sonnet | 78.2 |
| 12 | Gemini 1.5 Pro | 75.8 |
| 13 | Claude 3 Haiku | 72.9 |
| 14 | Gemini 1.5 Flash | 72.5 |
| 15 | Llama 3.1 8B | 68.8 |
Interactive version: theaggregate.ai/benchmark?slug=multi-if · How It Works · Data refreshed daily, snapshot 2026-09-05.