Phi 4 Mini

Phi 4 Mini Instruct is a lightweight (3.8B parameters) open model built upon synthetic data and filtered web data, focusing on high-quality reasoning. It supports a 128K token context length and is enhanced for instruction adherence and safety via supervised fine-tuning and direct preference optimization.

Benchmark results

Benchmark Score Tags Source
ARC-C 83.7% self-reported llm-stats link →
Arena Hard 32.8% self-reported llm-stats link →
BIG-Bench Hard 70.4% self-reported llm-stats link →
BoolQ 81.2% self-reported llm-stats link →
GPQA 25.2% self-reported llm-stats link →
GSM8k 88.6% self-reported llm-stats link →
HellaSwag 69.1% self-reported llm-stats link →
MATH 64.0% self-reported llm-stats link →
MGSM 63.9% self-reported llm-stats link →
MMLU 67.3% self-reported llm-stats link →
MMLU-Pro 52.8% self-reported llm-stats link →
Multilingual MMLU 49.3% self-reported llm-stats link →
OpenBookQA 79.2% self-reported llm-stats link →
PIQA 77.6% self-reported llm-stats link →
Social IQa 72.5% self-reported llm-stats link →
TruthfulQA 66.4% self-reported llm-stats link →
Winogrande 67.0% self-reported llm-stats link →