HumanEval-ER

A variant of the HumanEval benchmark that measures functional correctness for synthesizing programs from docstrings, consisting of 164 original programming problems assessing language comprehension, algorithms, and simple mathematics

Kimi K2 Instruct from Moonshot AI currently leads the HumanEval-ER leaderboard with a score of 0.811 across 1 evaluated AI models.

Paper

Moonshot AIKimi K2 Instruct leads with 81.1%.

Progress Over Time

Interactive timeline showing model performance evolution on HumanEval-ER

State-of-the-art frontier
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HumanEval-ER Leaderboard

1 models
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1
Moonshot AI
Moonshot AI
1.0T
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FAQ

Common questions about HumanEval-ER.

What is the HumanEval-ER benchmark?

A variant of the HumanEval benchmark that measures functional correctness for synthesizing programs from docstrings, consisting of 164 original programming problems assessing language comprehension, algorithms, and simple mathematics

What is the HumanEval-ER leaderboard?

The HumanEval-ER leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Kimi K2 Instruct by Moonshot AI leads with a score of 0.811. The average score across all models is 0.811.

What is the highest HumanEval-ER score?

The highest HumanEval-ER score is 0.811, achieved by Kimi K2 Instruct from Moonshot AI.

How many models are evaluated on HumanEval-ER?

1 models have been evaluated on the HumanEval-ER benchmark, with 0 verified results and 1 self-reported results.

Where can I find the HumanEval-ER paper?

The HumanEval-ER paper is available at https://arxiv.org/abs/2107.03374. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does HumanEval-ER cover?

HumanEval-ER is categorized under reasoning. The benchmark evaluates text models.

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