PhiBench

PhiBench is an internal benchmark designed to evaluate diverse skills and reasoning abilities of language models, covering a wide range of tasks including coding (debugging, extending incomplete code, explaining code snippets) and mathematics (identifying proof errors, generating related problems). Created by Microsoft's research team to address limitations of standard academic benchmarks and guide the development of the Phi-4 model.

Phi 4 Reasoning Plus from Microsoft currently leads the PhiBench leaderboard with a score of 0.742 across 3 evaluated AI models.

Paper

MicrosoftPhi 4 Reasoning Plus leads with 74.2%, followed by MicrosoftPhi 4 Reasoning at 70.6% and MicrosoftPhi 4 at 56.2%.

Progress Over Time

Interactive timeline showing model performance evolution on PhiBench

State-of-the-art frontier
Open
Proprietary

PhiBench Leaderboard

3 models
ContextCostLicense
114B
214B
3
Microsoft
Microsoft
15B16K$0.07 / $0.14
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FAQ

Common questions about PhiBench.

What is the PhiBench benchmark?

PhiBench is an internal benchmark designed to evaluate diverse skills and reasoning abilities of language models, covering a wide range of tasks including coding (debugging, extending incomplete code, explaining code snippets) and mathematics (identifying proof errors, generating related problems). Created by Microsoft's research team to address limitations of standard academic benchmarks and guide the development of the Phi-4 model.

What is the PhiBench leaderboard?

The PhiBench leaderboard ranks 3 AI models based on their performance on this benchmark. Currently, Phi 4 Reasoning Plus by Microsoft leads with a score of 0.742. The average score across all models is 0.670.

What is the highest PhiBench score?

The highest PhiBench score is 0.742, achieved by Phi 4 Reasoning Plus from Microsoft.

How many models are evaluated on PhiBench?

3 models have been evaluated on the PhiBench benchmark, with 0 verified results and 3 self-reported results.

Where can I find the PhiBench paper?

The PhiBench paper is available at https://arxiv.org/abs/2412.08905. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does PhiBench cover?

PhiBench is categorized under general, math, and reasoning. The benchmark evaluates text models.

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