--- title: "evals vs ai-berkshire" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openai-evals-vs-xbtlin-ai-berkshire" tools: ["openai-evals", "xbtlin-ai-berkshire"] --- # evals vs ai-berkshire *GraphCanon updated Jul 11, 2026* ## Verdict Pick evals if evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations; pick ai-berkshire if ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and. [evals](https://github.com/openai/evals) reports 19k GitHub stars, 3.0k forks, and 217 open issues, last pushed Apr 14, 2026. [ai-berkshire](https://github.com/xbtlin/ai-berkshire#readme) has 13k stars, 1.8k forks, and 17 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [evals's repository](https://github.com/openai/evals) and [ai-berkshire's repository](https://github.com/xbtlin/ai-berkshire). | | [evals](/tools/openai-evals.md) | [ai-berkshire](/tools/xbtlin-ai-berkshire.md) | | --- | --- | --- | | Tagline | Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks. | AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis. | | Stars | 18,890 | 12,711 | | Forks | 3,017 | 1,803 | | Open issues | 217 | 17 | | Language | Python | Python | | Adopt for | Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations. | ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [evals](/tools/openai-evals.md) | [ai-berkshire](/tools/xbtlin-ai-berkshire.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 87d | 0d | | Open issues (now) | 217 | 17 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/openai-evals/trust.md) | [trust report](/tools/xbtlin-ai-berkshire/trust.md) | ## Decision facts: evals - **Adopt for:** Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations. ## Decision facts: ai-berkshire - **Adopt for:** ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's ## Choose when ### Choose evals if… - License: evals is Other, ai-berkshire is MIT. - Tags unique to evals: llm systems, large-language-models, use case testing, open-source. - * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem. ### Choose ai-berkshire if… - License: ai-berkshire is MIT, evals is Other. - Tags unique to ai-berkshire: investment-research, ai, portfolio-management, value-investing. - Also covers AI Agents. - You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies. ## When NOT to use evals - * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. - * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a繁 ## When NOT to use ai-berkshire - If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. - When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies. ## Common questions ### What is the difference between evals and ai-berkshire? evals: Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.. ai-berkshire: AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.. See the comparison table for live GitHub stats and shared categories. ### When should I choose evals over ai-berkshire? Choose evals over ai-berkshire when License: evals is Other, ai-berkshire is MIT; Tags unique to evals: llm systems, large-language-models, use case testing, open-source; * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem. ### When should I choose ai-berkshire over evals? Choose ai-berkshire over evals when License: ai-berkshire is MIT, evals is Other; Tags unique to ai-berkshire: investment-research, ai, portfolio-management, value-investing; Also covers AI Agents; You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies. ### When should I avoid evals? * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a繁 ### When should I avoid ai-berkshire? If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies. ### Is evals or ai-berkshire more popular on GitHub? evals has more GitHub stars (18,890 vs 12,711). Stars measure visibility, not whether either tool fits your constraints. ### Are evals and ai-berkshire open source? Yes - both are open-source projects on GitHub (evals: Other, ai-berkshire: MIT). ### Where can I find alternatives to evals or ai-berkshire? GraphCanon lists graph-backed alternatives at [evals alternatives](/tools/openai-evals/alternatives) and [ai-berkshire alternatives](/tools/xbtlin-ai-berkshire/alternatives) ([evals markdown twin](/tools/openai-evals/alternatives.md), [ai-berkshire markdown twin](/tools/xbtlin-ai-berkshire/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/openai-evals-vs-xbtlin-ai-berkshire.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, evals or ai-berkshire? evals: Steady. ai-berkshire: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for evals and ai-berkshire? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [evals trust report](/tools/openai-evals/trust); [ai-berkshire trust report](/tools/xbtlin-ai-berkshire/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openai-evals`](/api/graphcanon/graph?tool=openai-evals) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_