BIG-bench
Benchmark for probing large language models and extrapolating their future capabilities
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is BIG-bench?
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.
Key differentiator
“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.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Core documentation focuses on basic setup and common tasks, lacks in-depth guides for complex configurations
Benchmarking large language models can lead to high memory usage and slow processing times
Fit analysis
Who is it for?
✓ Best 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
✕ Not a fit for
Teams needing real-time performance metrics for production systems
Projects that require proprietary or closed-source benchmarks
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Integrations
Next step
Get Started with BIG-bench
Step-by-step setup guide with code examples and common gotchas.