Hallucination Leaderboard vs Promptfoo
Side-by-side comparison of two AI agent tools
Short answer
- Promptfoo is growing faster: +1,110 GitHub stars in the last 30 days vs +25 for Hallucination Leaderboard.
- Pick Hallucination Leaderboard for: leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents. Pick Promptfoo for: open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps.
From GitHub data refreshed daily.
Hallucination Leaderboardopen-source
Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents
Promptfooopen-source
Open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps
Metrics
| Hallucination Leaderboard | Promptfoo | |
|---|---|---|
| Stars | 3.3k | 25.7k |
| Star velocity /mo | 24.947368421052634 | 1.1k |
| Commits (90d) | 2 | 920 |
| Releases (6m) | 0 | 10 |
| Downloads (30d, npm + PyPI) | — | 3.0M |
| Overall score | 0.3884668157765224 | 0.8639349362705032 |
Pros
- +Regularly updated with latest model versions and performance data, ensuring current relevance for model selection decisions
- +Uses standardized HHEM evaluation methodology providing consistent and comparable metrics across all tested models
- +Comprehensive metrics beyond just hallucination rates including factual consistency, answer rates, and summary length statistics
- +Comprehensive testing suite covering both performance evaluation and security red teaming in a single tool
- +Multi-provider support with easy comparison between OpenAI, Anthropic, Claude, Gemini, Llama and dozens of other models
- +Strong CI/CD integration with automated pull request scanning and code review capabilities for production deployments
Cons
- -Limited to summarization tasks only, not covering other common LLM use cases like code generation or creative writing
- -No API access mentioned for programmatic integration into model selection workflows
- -Requires API keys and credits for multiple LLM providers, which can become expensive for extensive testing
- -Command-line focused interface may have a learning curve for teams preferring GUI-based tools
- -Limited to evaluation and testing - does not provide actual LLM application development capabilities
Use Cases
- •Selecting the most reliable LLM for production summarization applications where factual accuracy is critical
- •Academic research into hallucination patterns and model reliability across different architectures and training approaches
- •Benchmarking new models against established baselines to evaluate improvements in factual consistency
- •Automated testing and evaluation of prompt performance across different models before production deployment
- •Security vulnerability scanning and red teaming of LLM applications to identify potential risks and compliance issues
- •Systematic comparison of model performance and cost-effectiveness to optimize AI application architecture
FAQ
- Which is more popular, Hallucination Leaderboard or Promptfoo?
- Promptfoo has more GitHub stars (25,665 vs 3,316).
- Which is more actively developed, Hallucination Leaderboard or Promptfoo?
- Promptfoo had more commits in the last 90 days (920 vs 2).
- Should I use Hallucination Leaderboard or Promptfoo?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.