API-Bank

A comprehensive benchmark for tool-augmented LLMs that evaluates API planning, retrieval, and calling capabilities. Contains 314 tool-use dialogues with 753 API calls across 73 API tools, designed to assess how effectively LLMs can utilize external tools and overcome obstacles in tool leveraging.

Llama 3.1 405B Instruct from Meta currently leads the API-Bank leaderboard with a score of 0.920 across 3 evaluated AI models.

Paper

MetaLlama 3.1 405B Instruct leads with 92.0%, followed by MetaLlama 3.1 70B Instruct at 90.0% and MetaLlama 3.1 8B Instruct at 82.6%.

Progress Over Time

Interactive timeline showing model performance evolution on API-Bank

State-of-the-art frontier
Open
Proprietary

API-Bank Leaderboard

3 models
ContextCostLicense
1405B
270B
38B
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FAQ

Common questions about API-Bank.

What is the API-Bank benchmark?

A comprehensive benchmark for tool-augmented LLMs that evaluates API planning, retrieval, and calling capabilities. Contains 314 tool-use dialogues with 753 API calls across 73 API tools, designed to assess how effectively LLMs can utilize external tools and overcome obstacles in tool leveraging.

What is the API-Bank leaderboard?

The API-Bank leaderboard ranks 3 AI models based on their performance on this benchmark. Currently, Llama 3.1 405B Instruct by Meta leads with a score of 0.920. The average score across all models is 0.882.

What is the highest API-Bank score?

The highest API-Bank score is 0.920, achieved by Llama 3.1 405B Instruct from Meta.

How many models are evaluated on API-Bank?

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

Where can I find the API-Bank paper?

The API-Bank paper is available at https://arxiv.org/abs/2304.08244. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does API-Bank cover?

API-Bank is categorized under tool calling and reasoning. The benchmark evaluates text models.

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