UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

Catch your AI's mistakes and blind spots before your customers or regulators do. iFixAi runs 45 inspections, 32 graded core plus 13 extended for frontier risks like sabotage, sandbagging, and oversight evasion. It returns a letter grade in under 5 minutes. Industry and model agnostic.

Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.

build and benchmark deep research

Ranking LLMs on agentic tasks

Agentic AI research papers, benchmarks, frameworks, and tools curated across 24 domains.

Vivaria is METR's tool for running evaluations and conducting agent elicitation research.

one click to open multi AI sites ｜ 一键打开多个 AI 站点，查看 AI 结果

Statistical analysis methods for comparing prompt and model performance in LLM evaluations.

☑️ A curated list of tools, methods & platforms for evaluating AI reliability in real applications

Code scanner to check for issues in prompts and LLM calls

Every Eval Ever is a shared schema and crowdsourced eval database. It defines a standardized metadata format for storing AI evaluation results — from leaderboard scrapes and research papers to local evaluation runs — so that results from different frameworks can be compared, reproduced, and reused.

A benchmark for AI-driven CAD generation and editing

Comprehensive AI Model Evaluation Framework with advanced techniques including Temperature-Controlled Verdict Aggregation via Generalized Power Mean. Support for multiple LLM providers and 15+ evaluation metrics for RAG systems and AI agents.

Make your OpenClaw agents better, cheaper, and faster.

Benchmark evaluating LLMs on their ability to create and resist disinformation. Includes comprehensive testing across major models (Claude, GPT-4, Gemini, Llama, etc.) with standardized evaluation metrics.

Bring Galileo powered eval workflows into Claude Code and Codex.

⚡️ The "1-Minute RAG Audit" — Generate QA datasets & evaluate RAG systems in Colab, Jupyter, or CLI. Privacy-first, async, visual reports.

FinMTM: A Multi-Turn Multimodal Benchmark for Financial Reasoning and Agent Evaluation

Example Projects integrated with Future AGI Tech Stack for easy AI development