OpenAI Evals
by Community
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
OSS
OpenAI Evals
Added 1 June 2026
Overview
OpenAI Evals is a Python framework for systematically evaluating language models and LLM-based systems against benchmarks. It provides a registry of pre-built evaluation tasks and a structure for defining custom evaluation logic, enabling developers to measure model performance on specific capabilities.
Best for
Best for
Teams building LLM applications who need systematic, reproducible evaluation workflows
Use cases
- Comparing model outputs across different LLM versions or providers
- Measuring performance on domain-specific tasks before deployment
- Building custom evaluation suites for proprietary use cases
Notes
OpenAI Evals is a Python framework for systematically evaluating language models and LLM-based systems against benchmarks. It provides a registry of pre-built evaluation tasks and a structure for defining custom evaluation logic, enabling developers to measure model performance on specific capabilities.
18,584 stars on GitHub. Last updated 2026-04-14.
Use cases
- Comparing model outputs across different LLM versions or providers
- Measuring performance on domain-specific tasks before deployment
- Building custom evaluation suites for proprietary use cases
Pros
- Open-source with active community contributions and 18k+ GitHub stars
- Extensible framework for defining custom evaluation logic beyond built-in benchmarks
- Direct integration path with OpenAI models
Cons
- Requires manual setup and Python expertise to implement evaluations
- Registry of benchmarks may not cover all specialized domains
- Evaluation design quality depends on how well you define success criteria
Indexed from awesome-llm and enriched against its public facts.
Pros
- Open-source with active community contributions and 18k+ GitHub stars
- Extensible framework for defining custom evaluation logic beyond built-in benchmarks
- Direct integration path with OpenAI models
Cons
- Requires manual setup and Python expertise to implement evaluations
- Registry of benchmarks may not cover all specialized domains
- Evaluation design quality depends on how well you define success criteria
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
awesome-hallucination-detection
Community
List of papers on hallucination detection in LLMs.
awesome-language-model-analysis
Community
This paper list focuses on the theoretical and empirical analysis of language models, especially large language models (LLMs). The papers in this list investigate the learning beha
Awesome-LLM-hallucination
Community
LLM hallucination paper list
Awesome LLM Security
Community
A curation of awesome tools, documents and projects about LLM Security.
Berkeley Function-Calling Leaderboard
Community
Explore The Berkeley Function Calling Leaderboard (also called The Berkeley Tool Calling Leaderboard) to see the LLM
GPT-4 Technical Report
Community
2023-03
LLMEval
Community
LLMEval is a research series dedicated to building comprehensive, fair, and robust evaluation frameworks for large language models.
Neurips2022-Foundational Robustness of Foundation Models
Community
NeurIPS Tutorial Foundational Robustness of Foundation Models
OLMO-eval
Community
Evaluation suite for LLMs
WHOOPS!
Community
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images
ACLUE
Community
Official github repo for ACLUE, an evaluation benchmark focused on ancient Chinese language comprehension
AlpacaEval
Community
AlpacaEval Leaderboard
Chain-of-Thought Hub
Community
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
Chinese Large Model Leaderboard
Community
非线智能 NoneLinear - ReLE评测：中文AI大模型能力评测（持续更新）：目前已囊括374个大模型，覆盖chatgpt、gpt-5.4、谷歌gemini-3.1-pro、Claude-4.6、文心ERNIE-X1.1、ERNIE-5.0、qwen3.6-max、qwen3.6-plus、百川、讯飞星火、商汤senseChat等商用模型， 以及st
CompassRank
Community
评测榜单旨在为大语言模型和多模态模型提供全面、客观且中立的得分与排名，同时提供多能力维度的评分参考，以便用户能够更全面地了解大模型的能力水平。
Giskard
Community
🐢 Open-Source Evaluation & Testing library for LLM Agents
HELM
Community
Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducib
instruct-eval
Community
This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.
lm-evaluation-harness
Community
A framework for few-shot evaluation of language models.
M3CoT
Community
Leaderboard | M 3 CoT
MathEval
Community
a comprehensive benchmarking platform designed to evaluate large models' mathematical abilities across 20 fields and nearly 30,000 math problems.
OLMO-eval
Community
Evaluation suite for LLMs
Open LLM Leaderboard
Community
Track, rank and evaluate open LLMs and chatbots
promptfoo
Community
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative config
Ragas
Community
Supercharge Your LLM Application Evaluations 🚀
simple-evals
Community
Eval tools by OpenAI.
TensorZero
Community
TensorZero builds open-source tools for production-grade LLM applications: LLM gateway, observability, optimization, evaluations, and experimentation.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.