// BENCHMARK

Multi-IF benchmark

AI model leaderboard for the Multi-IF benchmark. Compare how large language models score on Multi-IF, see the full ranking, and understand what this AI benchmark measures. Qwen3-14B currently leads with 74.8. Multilingual instruction-following benchmark — IFEval-style prompts in 8 languages.

Leaderboard

# Model Organization Score Variant Source
#1 Qwen3-14B Qwen 74.8 thinking official ↗
#2 Qwen3-32B Qwen 73 thinking official ↗
#3 Qwen3-14B Qwen 72.9 non-thinking official ↗
#4 Qwen3-30B-A3B Qwen 72.2 thinking official ↗
#5 Qwen3-235B-A22B Qwen 71.9 thinking official ↗
#6 Qwen3-8B Qwen 71.2 thinking official ↗
#7 Qwen3-30B-A3B Qwen 70.8 non-thinking official ↗
#8 Qwen3-32B Qwen 70.7 non-thinking official ↗
#9 Qwen3-235B-A22B Qwen 70.2 non-thinking official ↗
#10 Qwen3-8B Qwen 69.2 non-thinking official ↗
#11 Qwen3-4B Qwen 66.3 thinking official ↗
#12 Qwen3-4B Qwen 61.3 non-thinking official ↗
#13 Qwen3-1.7B Qwen 51.2 thinking official ↗
#14 Qwen3-1.7B Qwen 44.7 non-thinking official ↗
#15 Qwen3-0.6B Qwen 36.1 thinking official ↗
#16 Qwen3-0.6B Qwen 33.3 non-thinking official ↗

Frequently asked questions about Multi-IF

What is the Multi-IF benchmark?

Multilingual instruction-following benchmark — IFEval-style prompts in 8 languages.

How is the Multi-IF benchmark scored?

Multi-IF is scored using the accuracy metric, where a higher score is better. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.

Which AI model scores highest on Multi-IF?

As of the latest reported scores on GenAIList, Qwen3-14B achieves the highest result on Multi-IF with a score of 74.8.

Is a higher Multi-IF score better?

Yes. On Multi-IF a higher score indicates better performance, so models near the top of the leaderboard are the strongest.