Evaluation & TestingBIG-bench
Benchmark for probing large language models and extrapolating their future capabilities
- Status
- UnmaintainedGitHub repository has been archived.
- Last checked
- Checked · Oct 10, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
BIG-bench is a collaborative benchmark designed to evaluate the performance of large language models across various tasks, providing insights into their current abilities and potential future advancements.
BIG-bench stands out as an open, collaborative benchmark specifically designed for evaluating large language models, offering a comprehensive suite of tasks to assess model capabilities and future potential.
When it fits — and when it doesn’t
A good fit for
Academic researchers looking to benchmark and compare the capabilities of large language models
Developers who need a comprehensive set of tasks to evaluate model performance across various domains
Look elsewhere if
Teams needing real-time performance metrics for production systems
Projects that require proprietary or closed-source benchmarks
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited documentation for advanced usage scenarios
Core documentation focuses on basic setup and common tasks, lacks in-depth guides for complex configurations
- 02
Performance bottlenecks with very large datasets
Benchmarking large language models can lead to high memory usage and slow processing times
What it does well
Collaborative benchmark for large language models
Evaluation across diverse tasks to assess model capabilities
Open-source and community-driven
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up BIG-bench
Setup steps, common gotchas and what to check after 30 days.